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The article describes the revolutionary new ways of communicating the written word when moving from the Medieval to Modern period in Europe, primarily the use of paper and moveable typeface printing and how these catalysed important cultural developments. A similar revolution has taken place in the last 50 years with the development of the internet. The article looks at how scientific publishing has changed with electronic publishing, including the development of Open Access. The journal Heritage Science is placed into this context. Especially important for scientific journals in an era when anyone can post anything on a webpage, is maintaining standards through high quality refereeing which distinguishes formal scientific literature from informal websites. [ABSTRACT FROM AUTHOR]

This paper aims to examine research practice and performance on the electronics resources in India during the year 2011 to 2020 on different parameters namely yearly research growth, relative growth rate and doubling time, forms of research, most prolific authors and Institutions, Collaborative country, degree of collaboration, and funding agency etc. The data of the current research paper about electronic resources indexed in the Scopus database have been retrieved. The records with topic search (includes Title, Abstract, Keywords and Keywords Plus) "Electronic resources" were extracted. MS Excel and VOS viewer have analyzed these data. The search result shows that a total of 1482 papers have indexed in the Scopus database during 2011-2020. The study reveals that numerous research papers have been published on electronic resources in India. 2019 is the leading (288 papers) producer of research papers," Library Philosophy and Practice" is the leading (64 papers) source of publications, Bhat, N.A, Jha, M.K and Thanuskodi, S are the prolific authors, the United States is the highest (78 Papers) collaborated country and degree of collaboration (DC) = 0.92, "Department of Science and Technology, Government of Kerala" is the highest (13 papers) funding agency for the topic electronic resources research in India. [ABSTRACT FROM AUTHOR]

Background: Brucellosis produces losses in livestock raising in the Americas. This region reports prevalence variations associated with the implementation of control programs, thus requiring an analysis that permits the combination of results to reach conclusions, which may be conducted through meta-analysis. Aim. To estimate the combined prevalence of Brucellosis in Cattle and Buffaloes in Central America and the Caribbean, and South America in the 2010-2021 period, and to analyze the different time performances in all the regions and the species. Materials and methods: Several papers published in electronic databases, such as PubMed / PubMed Central, Science Direct, Scielo, Ebsco, and Google Scholar were selected. Original papers and postgraduate theses available were included, provided they offered information about cattle and buffaloes, using the serological techniques recommended by the World Animal Health Organization, and which provided the sample size and the number of positives. A meta-analysis was done to estimate the combined prevalence of the disease, and the effect on the subgroups was evaluated by meta-regression. Results: Overall, 65 that met the selection criteria were included, 56 related to cattle, and 11 to buffaloes. The combined prevalence was 3.0%; differences between cattle (2.7%) and buffaloes (5.2%) were observed. The differences between the periods studied accounted for 4.3% (2011-2016) and 2.0% (2017-2021), respectively. Conclusions: The combined prevalence of the disease was 3.0%, which was higher in buffaloes, which dropped in the last five years. No differences were observed between the two regions studied. [ABSTRACT FROM AUTHOR]

Twitter, a microblogging platform, has developed into an increasingly invaluable information source, where millions of users post a great quantity of tweets with various topics per day. Heterogeneous information networks consisting of multi-type objects and relations are becoming more and more prevalent as an organization form of knowledge and information. The task of linking an entity mention in a tweet with its corresponding entity in a heterogeneous information network is of great importance, for the purpose of enriching heterogeneous information networks with the abundant and fresh knowledge embedded in tweets. However, the entity mention is ambiguous. Additionally, tweets are short and informal, making it difficult to mine enough information from a single tweet for entity linking. In this paper, we propose an unsupervised iterative clustering framework TELHIN to link multiple similar tweets with a heterogeneous information network jointly. Our framework takes three dimensions of tweet similarity into consideration: (1) content similarity, (2) temporal similarity, and (3) user similarity. The appropriate weights of different similarity dimensions for each entity mention are learned iteratively based on the metric learning algorithm by leveraging the pairwise constraints generated automatically. Experiments on real data demonstrate the effectiveness of our framework in comparison with the baselines. [ABSTRACT FROM AUTHOR]

Research papers are a repository of information on the various elements that make up science and technology R&D activities. Generating knowledge maps based on research papers enables identification of specific areas of scientific and technical research as well as understanding of the flow of knowledge between those areas. Recently, as the number of electronic publishing and informatics archives along with the amount of accumulated knowledge related to science and technology has proliferated, the need to utilize the meta-knowledge obtainable from research papers has increased. Therefore, this study devised a model based on meta-knowledge (i.e., text information including citations, abstracts, area codes) for prediction of future growth potential using deep learning algorithms and investigated the applicability of the various forms of meta-knowledge to the prediction of future growth potential. It also proposes how to select the promising technology clusters based on the proposed model. [ABSTRACT FROM AUTHOR]

Objective: To assess the association between Cannabis use and bladder cancer. Methods: A systematic literature review was performed using studies published in electronic databases including PubMed, MEDLINE, and Google Scholar. Due to the scarcity of literature on this topic, the search was not limited to a specific design, year of publication, or human studies. The studies were screened by two reviewers in the following steps; first, the studies were discovered according to the predetermined search strategy; second, the unrelated studies and duplicates were eliminated by screening the abstracts, titles, and keywords; third, the full text of relevant and eligible papers were critically appraised and assessed for the risk of bias using the respective tool. The two review authors independently assessed the risk of bias and outcome levels using the Newcastle-Ottawa Scale for the outcomes in observational studies. Any disagreements were settled by a third party. Results: The search strategy yielded 39 research articles. After removing 21 duplicates, 18 publications were eligible for title and abstract review. Thirteen studies were found to be irrelevant and subsequently excluded. Only three full-text articles were evaluated and included in the qualitative synthesis. Conclusions: The role of Cannabis in bladder cancer has been seldom studied. The small number of studies show contradictory findings; potential carcinogenic versus protective effect. The growing interest in Cannabis use after legalization necessitates further investigations with a robust design to assess the long-term effect of Cannabis on bladder cancer. [ABSTRACT FROM AUTHOR]

The Latin American journals of psychology indexed in the Journal of Citation Reports (JCR), are generally edited by professional associations of psychologists, universities and private foundations. This paper analyzes the positioning strategy adopted by the Professional Association of Psychologists of Madrid, regarding the psychological journals in the area in which they edit. The methodological approach taken to explore the topic uses socio-bibliometric techniques gathering numerical data, and then using that data to perform analyses for a well-informed description of what the topic might be. The results reveal that journals, whose editor or co-editor was Professional Association of Psychologists of Madrid, have increased their visibility in recent years, in both, the SCImago Journal Rank (SJR= 8 journals) and that of the Journal of Citation Reports (JCR= 7 journals) with a greater citation count for its articles, and a higher number of views and downloads for the papers published in its journals. The conclusion is, that the positioning strategy adopted by the Professional Association of Psychologists of Madrid was an effective one, involving the unification of certain rules relating to the edition of articles in their journals, the professionalization of editorial management, the electronic publishing with digital publication of journals and using the open access publishing model for scholarly communication that makes research information available to readers at no cost, as well as their integration in the list of international databases. Although a broader strategy concerning gender equality is recommended, the Spanish professional association of psychologists still stands today as the main editorial group of psychological journals indexed in JCR and SJR of Spain [ABSTRACT FROM AUTHOR]

The purpose of this paper to examine the research paper which are to publish in The Electronic Library (TEL) during 2010-2018. There are 533 articles and 1249 authors were analyzed by year wise dispersion of research articles, author productivity, authorship pattern volume wise authorship pattern and degree of collaboration. It is the widely used aspect of bibliometric analysis. The highest of 72 (13.50%) paper were published in 2017 and 2018 and lowest of 49 (9.20%) in 2013. We found that degree of collaboration of this Journal is 0.756. [ABSTRACT FROM AUTHOR]

Most recent approaches for Text Simplification (TS) have drawn on insights from machine translation to learn simplification rewrites from the monolingual parallel corpus of complex and simple sentences, yet their effectiveness strongly relies on large amounts of parallel sentences. However, there has been a serious problem haunting TS for decades, that is, the availability of parallel TS corpora is scarce or not fit for the learning task. In this paper, we will focus on one especially useful and challenging problem of unsupervised TS without a single parallel sentence. To the best of our knowledge, we present the first unsupervised text simplification system based on phrase-based machine translation system, which leverages a careful initialization of phrase tables and language models. On the widely used WikiLarge and WikiSmall benchmarks, our system respectively obtains 39.08 and 25.12 SARI points, even outperforms some supervised baselines. [ABSTRACT FROM AUTHOR]

In the sharing economy system, consumer-to-consumer product-exchange (C2C-PE) for digital products is commonly seen. In this paper, we analytically explore the C2C-PE problem for digital products. To be specific, we consider the presence of a digital product developer (DPD) who develops and sells a product to consumers in the market. Consumers possess random valuation toward the digital product and the DPD needs to decide the optimal selling price for the product. We study the impacts brought by C2C-PE. We try to uncover whether (and when) DPDs and consumers will be benefited by the presence of C2C-PE. In the basic model, when all parties are risk neutral, we find that the presence of C2C-PE is always beneficial to the DPD and consumers. To show the robustness of results in the basic model, we further extend the analysis to cover a few cases and prove that this conclusion holds irrespective of the DPD’s risk averse attitude, the consumers’ risk averse attitude, as well as whether the utility gained from C2C-PE is effort dependent or not. Hence, we conclude that C2C-PE, which seems to be harmful to DPDs, is in fact a beneficial scheme to both the DPDs and consumers. [ABSTRACT FROM AUTHOR]

User Generated Categories (UGCs) are short but informative phrases that reflect how people describe and organize entities. UGCs express semantic relations among entities implicitly hence serve as a rich data source for knowledge harvesting. However, most UGC relation extraction methods focus on English and heavily rely on lexical and syntactic patterns. Applying them directly to Chinese UGCs poses significant challenges because Chinese is an analytic language with flexible language expressions. In this paper, we aim at harvesting fine-grained relations from Chinese UGCs automatically. Based on neural networks and negative sampling, we introduce two word embedding projection models to identify is-a relations. The accuracy of prediction results is improved via a collective refinement algorithm and a hypernym expansion method. We further propose a graph clique mining algorithm to harvest non-taxonomic relations from UGCs, together with their textual patterns. Two experiments are conducted to validate our approach based on Chinese Wikipedia. The first experiment verifies the is-a relation extraction approach achieves high accuracy, outperforming state-of-the-art methods. The second experiment shows that the proposed method can harvest non-taxonomic relations of large quantity and high accuracy, with minimal human intervention. [ABSTRACT FROM AUTHOR]

Background: Residency programs generally carry out various educational interventions to improve residents' publication records. Since an intervention may not produce the same effect in different locations, evaluating the effectiveness of individual interventions is essential for examining progress in this field of study. Authorities at the Tabriz University of Medical Science (TUOMS) proposed a research training program targeting a rise in residents' scholarly activity and publications; this study aimed to evaluate the program and share the findings and experiences. Methods: Questionnaires were sent to 182 residents and the heads of all clinical departments. Evaluators used Kirkpatrick's four-level model and Stufflebeam's Context, Input, Process and Product model for data gathering and analyzing. Focus group discussions (FGDs) and in-depth semi-structured interviews were done with faculty members, executive staff, and residents to complement the survey results. Data were summarized and categorized using quantitative and qualitative analysis. Results: The participation rate for residents and heads of departments were 76 (41.7%) and 14 (70%), respectively. At the end of the course, residents assessed their knowledge and research skills as weak or medium in most of the subjects. A total of 182 (100 %) residents prepared thesis proposals. Only 82 (49.1%) residents completed their thesis, and 19 (11.3%) published papers. Generally, participants were not satisfied with the course. Barriers noted were: mandatory topics for theses, an intensive course with a one-month duration, a lack of consideration of practical subjects, high cost of the course, and failure to achieve an increase in publications. Conclusion: The self-assessment results of increased knowledge and research skills did not indicate improvement. Mandatory participation in the course did not result in the expected publication increase. [ABSTRACT FROM AUTHOR]

Introduction. Open access to digital research output is increasing, but academic library policies can place restrictions on public access to libraries. This paper reports on a preliminary study to investigate the correlation between academic library access policies and institutional positions of openness to knowledge. Method. This primarily qualitative study used document and data analysis to examine the content of library access or use policies of twelve academic institutions in eight countries. The outcomes were statistically correlated with institutional open access publication policies and practices. Analysis. We used an automated search tool together with manual searching to retrieve Webbased library access policies, then categorised and counted the levels and conditions of public access. We compared scores for institutional library access feature with open access features and percentages of open access publications. Results. Academic library policies may suggest open public access but multi-layered user categories, privileges and fees charged can inhibit such access, with disparities in openness emerging between library policies and institutional open access policies. Conclusion. As open access publishing options and mandates expand, physical entry and access to print and electronic resources in academic libraries is contracting. This conflicts with global library and information commitments to open access to knowledge. [ABSTRACT FROM AUTHOR]

Enjoying widespread government support and encouragement for the digital projects of publishers and media industry. The Chinese publishing business continues to show steady development in the past year. At the same time, significant changes are taking place in the structure of the publishing industry. The content production, marketing, operating, and consumption are not linear upstream-downstream related any more. Instead, they have fused together, and thus formed a new industrial ecosphere. In this paper, we investigate the new technology research and practice in the digital publishing industry. There is obvious indication that new technology plays an important role in the structural change of the publishing industry. [ABSTRACT FROM AUTHOR]

As one of the fundamental tasks in text analysis, phrase mining aims at extracting quality phrases from a text corpus and has various downstream applications including information extraction/retrieval, taxonomy construction, and topic modeling. Most existing methods rely on complex, trained linguistic analyzers, and thus likely have unsatisfactory performance on text corpora of new domains and genres without extra but expensive adaption. None of the state-of-the-art models, even data-driven models, is fully automated because they require human experts for designing rules or labeling phrases. In this paper, we propose a novel framework for automated phrase mining, $\mathsf{AutoPhrase}$ , which supports any language as long as a general knowledge base (e.g., Wikipedia) in that language is available, while benefiting from, but not requiring, a POS tagger. Compared to the state-of-the-art methods, $\mathsf{AutoPhrase}$ has shown significant improvements in both effectiveness and efficiency on five real-world datasets across different domains and languages. Besides, $\mathsf{AutoPhrase}$ can be extended to model single-word quality phrases. [ABSTRACT FROM AUTHOR]

Books, as a representative of lengthy documents, convey rich semantics. Traditional document modeling methods, such as bag-of-words models, have difficulty capturing such rich semantics when only considering term-frequency features. In order to explore term spatial distributions over a book, a tree-structured book representation is investigated in this paper. Moreover, an efficient learning framework, Tree2Vector, is introduced for mapping tree-structured book data into vectorial space. In particular, we present two types of locality reconstruction (LR) models: Euclidean-type and cosine-type, during the transformation process of tree structures into vectorial representations. The LR is used for modeling the reconstruction process, in which each parent node in a tree is supposed to be reconstructed by its child nodes. The prominent advantage of this Tree2Vector framework is that it solely utilizes the local information within a single book tree. In addition, extensive experimental results demonstrate that Tree2Vector is able to deliver comparable or better performance in comparison to methods that consider the information of all trees in a database globally. Experimental results also suggest that cosine-type LR consistently performs better than Euclidean-type LR in applications of book and author recommendations. [ABSTRACT FROM AUTHOR]

From 1 July 2013 the EU Official Journal is published in electronic form through the EUR-Lex platform. Therefore, this platform is comprehensive source of authentic and non-authentic information regarding EU law. Despite this progress, that is however still not present in the Czech Republic, the EUR-Lex is facing occasional criticism because of the lack of userfriendliness and clarity. Isolated directive or other document can not be considered a legal information, but merely the legal datum. Given the specificity of the decisions of the Court of Justice of the EU, we are able to achieve communication of the resulting legal information only after linking the decision with the text of the respective directive. Therefore, access to these related documents should be extremely simple and should allow for easy orientation of the user. Currently, EUR-Lex does not provide this comfort as the case law related to its directive or regulation is displayed only by so-called celex number. In this paper we discuss the structure of celex number and the possibility to use existing XML structure maintained by EUR-Lex for automatization of some search functions. Our paper is based on the following premises:Relevant legal information includes the opinion of the advocate general, which is currently impossible to locate easily (these opinions are not present in the list of related documents). Relevant legal information is the information about existence of unresolved preliminary questions brought before the CJEU; however, this information can not be easily ascertained given the current form of displaying of the related documents. Based on existing metadata structure in which EUR-Lex operates (especially celex numbers as unique identifiers of individual documents), it is possible to automate some research operations and to fix the above mentioned shortcomings of the current search. [ABSTRACT FROM AUTHOR]

This research examines contemporary, independent publishing in the Pacific Northwest (USA and Canada). Through a series of interviews with small publishers in Seattle, Portland, and Vancouver, BC, this paper will investigate whether independent publishers, based outside of the major publishing hubs of New York and Toronto, believe they can: compete in the global publishing environment; help to promote and preserve regional cultures and identities; and maintain diversity in cultural output. It will also explore how independent presses see themselves situated in the national and international publishing arena and identify what structures are in place to support them to do so. Although the focus of the empirical research is the Pacific Northwest, this paper has been contextualised within national publishing discourse. [ABSTRACT FROM AUTHOR]

The paper presents an analytical study of the research output in e-publishing field on a series of scientometric indicators. As seen from Scopus database the total world output was 7010 publications published in 10 years during 2005-2014. The study found that e-publishing is still a young subject field growing at a slow pace, 3.41% CAGR growth and averaged 1.08 citations per paper. The body of research literature in this field is still in the early stage of its growth. Publication scatter in this field is still very high. The top 15 most productive organizations accounted for as small global publication share as 5.72% and as small global citation share as 12.73% during 2005-14. The average productivity rate per organization in 10 years was as low as 26.7, citation impact per paper was 2.41, h-index was 6.93 and international collaborative share as 23.44% during 2005-14. To build top research centres in e-publishing field, it is important that funding agencies at national and international level should aggressively start providing planned funding support to research organizations. [ABSTRACT FROM AUTHOR]

Introduction. This study explores the extent to which an institutional repository makes papers available and accessible on the open Web by using 170 journal articles housed in DigiNole Commons, the institutional repository at Florida State University. Method. To analyse the repository's impact on availability and accessibility, we conducted independent known-item title searches on both Google and Google Scholar (GS) to search for faculty publications housed in DigiNole Commons. Analysis. The extent to which the repository makes articles available and accessible was measured quantitatively and the findings that cannot be summarized with numbers were analysed qualitatively. Results. Google and Google Scholar searches provided links to DigiNole metadata for a total of 145 (85.3%) of 170 items, and to full texts for 96 (96%) of 100 items. With one exception, access to either metadata or full text required no more than three clicks. Conclusions. Overall, the results confirm the contribution of the institutional repository in making papers available and accessible. The results also reveal some impediments to the success of open access, including impediments linked to contractual arrangements between authors and publishers, impediments linked to policies, practices and technologies governing the repository itself, and the low level of faculty participation in the repository. [ABSTRACT FROM AUTHOR]

This paper studies the problem of mining named entity translations by aligning comparable corpora. Current state-of-the-art approaches mine a translation pair by aligning an entity graph in one language to another based on node similarity or propagated similarity of related entities. However, they, building on the assumption of “symmetry”, quickly deteriorate on “weakly” comparable corpora with some asymmetry. In this paper, we pursue two directions for overcoming relation and entity asymmetry respectively. The first approach starts from weakly comparable corpora (for high recall) then ensures precision by selective propagation only to entities of symmetric relations. The second approach starts from parallel corpora (for high precision) then enhances recall by extending the translation matrix based on node similarity and contextual similarity. Our experimental results on English-Chinese corpora show that both approaches are effective and complementary. Our combined approach outperforms the best-performing baseline in terms of F1-score by up to 0.28. [ABSTRACT FROM AUTHOR]

In this paper, we introduce “task trail” to understand user search behaviors. We define a task to be an atomic user information need, whereas a task trail represents all user activities within that particular task, such as query reformulations, URL clicks. Previously, web search logs have been studied mainly at session or query level where users may submit several queries within one task and handle several tasks within one session. Although previous studies have addressed the problem of task identification, little is known about the advantage of using task over session or query for search applications. In this paper, we conduct extensive analyses and comparisons to evaluate the effectiveness of task trails in several search applications: determining user satisfaction, predicting user search interests, and suggesting related queries. Experiments on large scale data sets of a commercial search engine show that: (1) Task trail performs better than session and query trails in determining user satisfaction; (2) Task trail increases webpage utilities of end users comparing to session and query trails; (3) Task trails are comparable to query trails but more sensitive than session trails in measuring different ranking functions; (4) Query terms from the same task are more topically consistent to each other than query terms from different tasks; (5) Query suggestion based on task trail is a good complement of query suggestions based on session trail and click-through bipartite. The findings in this paper verify the need of extracting task trails from web search logs and enhance applications in search and recommendation systems. [ABSTRACT FROM AUTHOR]

Digital Object Identifier (DOI) has been internationally recognized as a standard for identifying information resources on the web. It is an advanced tool that provides unique identification or permanent links to find specific journal articles and other information resources online. This paper discusses digital object identifier and their use in accessing online scholarly materials in Africa. It looks at the extent of Uniform Resource Locators (URL), understanding DOI functionalities, and benefits of DOI, scholarly materials with DOI in Africa with a critical examination of African Online Journals (AJOL) which is the biggest database in Africa. It was therefore discovered that the use and application of DOI in accessing online scholarly materials of African origin is still at crawling stage. The study recommends that the publishers in Africa should take advantage of this development by doing the needful and emulate those journals in African Online Journals (AJOL) to register their publications for DOI. This will enhance wider visibility and easy retrieval of African scholarly materials, while African authors also needs to wake up to explore the benefit of the DOI. [ABSTRACT FROM AUTHOR]

Heterogeneous information networks that consist of multi-type, interconnected objects are becoming increasingly popular, such as social media networks and bibliographic networks. The task of linking named entity mentions detected from unstructured Web text with their corresponding entities in a heterogeneous information network is of practical importance for the problem of information network population. This task is challenging due to name ambiguity and limited knowledge existing in the network. Most existing entity linking methods focus on linking entities with Wikipedia and cannot be applied to our task. In this paper, we present SHINE+, a general framework for linking named entitieS in Web free text with a Heterogeneous I nformation NEtwork. We propose a probabilistic linking model, which unifies an entity popularity model with an entity object model. As the entity knowledge contained in the information network is insufficient, we propose a knowledge population algorithm to iteratively enrich the network entity knowledge by leveraging the context information of mentions mapped by the linking model with high confidence, which subsequently boosts the linking performance. Experimental results over two real heterogeneous information networks (i.e., DBLP and IMDb) demonstrate the effectiveness and efficiency of our proposed framework in comparison with the baselines. [ABSTRACT FROM PUBLISHER]

Entity linking is one of the problems to be handled in order to process natural language and to enrich the existing unstructured text with metadata. The generation of assignments between knowledge base entities and lexical units is called entity linking. Although a number of systems have been proposed for linking entity mentions in various languages, there is currently no publicly available entity linking system specific to the Turkish language. This paper presents a novel entity linking system—THINKER - for linking Turkish content with entities defined in the Turkish dictionary (tdk.gov.tr) or Turkish Wikipedia (tr.wikipedia.org). Specifically, we first propose a novel machine learning based entity detection algorithm for the Turkish language. Then, we propose a collective disambiguation algorithm which utilizes a set of metrics for the linking task and, which is optimized using a genetic algorithm. The effectiveness of THINKER is validated empirically over generated data sets. The experimental results show that THINKER outperformed the state-of-the-art cross-lingual and multilingual entity linking systems in the literature. High entity linking performance (74.81 percent F1 score) is achieved by extending previous methods with some features specific to Turkish language and by developing a novel method that can learn better representations of entity embeddings. [ABSTRACT FROM PUBLISHER]

Introduction. This paper presents the issues and challenges faced by a university library in encouraging academics and researchers to adopt open access, specifically with respect to depositing publications in the institutional repository Method. Interviews were conducted with academics and researchers about their awareness of open access and their use of the university repository. An action research approach was used to address issues on a continual basis, and redesign the repository based on the findings. Analysis. The interview data were analysed using thematic content analysis, and the repository data were analysed using heuristic evaluation Results. Results show that researchers lack awareness of open access and its value, and that there is also confusion about publishers' copyright policies and researcher reputation. The lack of visibility and usability of the library-managed institutional repository was found to be an issue, as well as the need for subject repositories. The results informed a redesign of the repository and informed the library's strategies to promote scholarly communication literacy. Conclusion. Whilst librarians have been advocates of open access, researchers' understanding of it is still limited? they have other pressures in regard to their publishing outputs, which also limits their adoption of open access practices. [ABSTRACT FROM AUTHOR]

Named entities such as people, locations, and organizations play a vital role in characterizing online content. They often reflect information of interest and are frequently used in search queries. Although named entities can be detected reliably from textual content, extracting relations among them is more challenging, yet useful in various applications (e.g., news recommending systems). In this paper, we present a novel model and system for learning semantic relations among named entities from collections of news articles. We model each named entity occurrence with sparse structured logistic regression, and consider the words (predictors) to be grouped based on background semantics. This sparse group LASSO approach forces the weights of word groups that do not influence the prediction towards zero. The resulting sparse structure is utilized for defining the type and strength of relations. Our unsupervised system yields a named entities’ network where each relation is typed, quantified, and characterized in context. These relations are the key to understanding news material over time and customizing newsfeeds for readers. Extensive evaluation of our system on articles from TIME magazine and BBC News shows that the learned relations correlate with static semantic relatedness measures like WLM, and capture the evolving relationships among named entities over time. [ABSTRACT FROM PUBLISHER]

For students with print impairments, e-books offer great potential to remove barriers to information. However, for various reasons, not all e-books are fully accessible. Significant variability exists between different platforms and titles. To benchmark e-book accessibility, a group of library and disability professionals across the UK higher education sector organized a crowdsourced e-book accessibility audit, using simple criteria to capture end-user experiences. The audit can act as a framework for librarians and e-book providers to discuss accessibility and effect improvements. This audit was of 275 e-books from 65 publishers across 44 platforms, resulting in an interactive spreadsheet on the project website and individual feedback reports for each platform. Most of the volunteer auditors had little accessibility expertise so a byproduct of the process was training to introduce key accessibility concepts and support for those using the audit tool. This paper explores the process, including key findings from a follow-up questionnaire for testers. The results indicate increased awareness of e-book accessibility and empathy for disabled learners and an appetite for further training, in particular using e-books with screen reading and text-to-speech software. The study suggests crowdsourced research can be highly effective on multiple levels. [ABSTRACT FROM AUTHOR]

The Digital Object Recognizer (DOR) is a system for identifying Persian digital objects on the web. DOR is a unique alphanumeric string assigned by Regional Information Center for Science and Technology (RICeST) to any entity to identify content and provide a persistent link to its location on the Internet digital networks. The paper describes the construction and functions of the DOR system for Persian articles and then introduces and outlines the underlying architecture regarding DOR system. The study concluded that using DOR will enable Iranian journal publishers assign it to both print and electronic journal articles; finally enumerated the benefits of DOI for stakeholders in the scholarly communication process. [ABSTRACT FROM AUTHOR]

New entities are being created daily. Though the novelty of these entities naturally attracts mentions, due to lack of prior knowledge, it is more challenging to collect knowledge about such entities than pre-existing entities, whose KBs are comprehensively annotated through LBSNs and EBSNs. In this paper, we focus on knowledge harvesting for emerging spatial entities (ESEs), such as new businesses and venues, assuming we have only a list of ESE names. Existing techniques for knowledge base (KB) harvesting are primarily associated with information extraction from textual corpora. In contrast, we propose a multimodal method for event detection based on the complementary interaction of image, text, and user information between multi-source platforms, namely Flickr and Twitter. We empirically validate our harvesting approaches improve the quality of KB with enriched place and event knowledge. [ABSTRACT FROM AUTHOR]

This paper investigates the difference in bullwhip effects in online and offline retail supply chains, offering insights into how frequent price discounts in e-commerce influence the bullwhip effect in the online retail supply chain. We consider a two-level online retail supply chain with a manufacturer and an online retailer in which the demand faced by the retailer is price sensitive and based on the price discount. Assuming that the online retailer employs an optimal order-up-to inventory policy with an optimal minimum mean-squared error forecasting technique, we derive the expression of the bullwhip effect in the online retail supply chain and make analysis and comparison. Finally, we develop a dual-channel supply chain model to directly observe the impact of price discounts in e-commerce on the bullwhip effect. The results suggest that price discounts in the online retail market generally amplify the bullwhip effect in the online retail supply chain, but in certain conditions, the bullwhip in the online supply chain may be smaller than that in the offline supply chain. We also find that the relationship between the lead time and the bullwhip effect in the online supply chain presents a distinctive feature contrary to the conclusions of previous studies. Based on the analysis, we develop important managerial insights regarding online retail supply chains. [ABSTRACT FROM AUTHOR]

This paper provides an overview of the e-book publishing industry in China and its changing business models. As the conventional publishing industry has continued to contract, digitization is becoming increasingly popular. Although China is an influential developing country undergoing rapid change, a dearth of research on its digital publishing industry exists at the present time. This article therefore explores two main research questions: (1) What are the recent trends and business models of digital publishing in China? (2) How might we evaluate the effectiveness and efficiency of such business models? To this end, multiple case studies are employed, as is the paradigm of structure-conduct-performance (SCP). It is proposed that Content plus App and Content plus Device are the basic business models for Chinese digital content producers and distributors. [ABSTRACT FROM AUTHOR]

The HHuLOA (Hull, Huddersfield, Lincoln Open Access) project is a two-year Jisc-funded project, which seeks to identify how open access (OA) support mechanisms can be used to assist with the development of research. One such area is policy landscape, which has shifted dramatically in the past two years. Many academic staff have been left confused, frustrated and stressed by new obligations placed upon long-established publishing practices and by the way in which these changes have been communicated. This paper describes the project's initial work undertaken in this area, with the aim of enabling academic audiences to better navigate the policy environment they find themselves in to comply and better understand the rights they have when using OA. [ABSTRACT FROM AUTHOR]

This paper reports on the contribution of the openness movement to the changing mode of distributing scholarly literature. It is argued that the University of Cape Town (UCT), a leading research university on the African continent with relatively high research output, has a social justice obligation to distribute freely its scholarly research to the widest audience possible. Contributing to this social justice obligation through the sharing of research output via open access (OA) platforms are the university's progressive OA policy and activities to ensure roll-out of the policy as well as its commitments to support article processing charges (APCs) and follow the global trend with regard to OA publishing. The authors, using a case study design, report that these factors have contributed to UCT's researchers adapting to publishing their journal articles on OA platforms. The investigation concludes that, in an era of fiscal constraints, the visibility of research is important to source funding and to meet the institution's social justice obligation; and therefore adapting to new publishing trends is an imperative for UCT researchers. [ABSTRACT FROM AUTHOR]

Power optimization has become a key challenge in the design of large-scale enterprise data centers. Existing research efforts focus mainly on computer servers to lower their energy consumption, while only few studies have tried to address data center networks (DCNs), which can account for 10-20 percent of the total energy consumption of a data center. In this paper, we propose CARPO, a correlation-aware power optimization algorithm that dynamically consolidates traffic flows onto a small set of links and switches in a DCN and then shuts down unused network devices for energy savings. In sharp contrast to existing work, CARPO is designed based on a key observation from the analysis of real DCN traces that the bandwidth demands of different flows do not peak at exactly the same time. As a result, if the correlations among flows are considered in consolidation, more energy savings can be achieved. In addition, CARPO integrates traffic consolidation with link rate adaptation for maximized energy savings. We implement CARPO on a hardware testbed composed of 10 virtual switches configured with a production 48-port OpenFlow switch and 8 servers. Our empirical results with traces from Wikipedia and Yahoo! data centers demonstrate that CARPO can save up to 50 percent of network energy for a DCN, while having only negligible delay increases. CARPO also outperforms two state-of-the-art baselines by 19.6 and 95 percent on energy savings, respectively. Our simulation results with a large-scale DCN also show that CARPO can achieve more energy savings than the baselines for typical DCN topologies, such as fat tree and BCube. [ABSTRACT FROM PUBLISHER]

The author shares his reflections about the future of scientific journals. Topics discussed include challenges being faced by the public library, the losing relevance of printed journals due to the rising popularity of virtual publications, and the tendency to ignore the anonymous reader. Also mentioned are reasons why the publishing of papers in English language is outdated, the call on publication channels to join sectoral networks, and the internationalization of scientific knowledge.

Paper highlights the current state of open access repositories (OARs) movement in Agricultural field of Asian countries. It describes their characteristics in terms of types, contents, disciplines, languages covered, technical and operational issues, and policy matters. Compares and evaluates repositories against selected parameters and makes some recommendations for the growth of agricultural repositories Worldwide. Also presents a unified interface that can harvest metadata from different OAI-PMH compliant agricultural repositories Worldwide. [ABSTRACT FROM AUTHOR]

Introduction. The aim of the research was to increase understanding of the state of e-book production in Lithuania and collect the data about the opinions of publishers regarding the future of e-books in the country. Method. A review of similar surveys in other countries was carried out and the research method was based on Winston's model of innovation diffusion. The questionnaire to publishers was prepared using the models of book publishing and distribution or book circuit developed by Murray and Squires. Data were collected by surveying respondents using paper and online questionnaires. Analysis. A quantitative descriptive statistical analysis was carried out, while open questions were analysed qualitatively looking for emerging topics. Results. More than half of active Lithuanian publishers completed the survey. Thirty per cent of those who answered the questionnaire publish e-books, but only six publishers had published a significant number of titles. The overall perception of other actors of the book market, such as libraries, book-sellers and self-publishing authors and others is positive. They are not regarded as a threat. The publishers do not expect rapid and significant growth of e-book market in Lithuania in the near future. Conclusions. The biggest hindrance to growth is a small size of the market and the lack of an export market for Lithuanian e-books. The demand of users for portable and convenient format and the use of new technologies in the educational system are the two biggest drivers in the development of ebook production. The user preference for traditional printed book is seen as one of the barriers for further development. Lithuanian publishers regard the market of e-books as rather uncertain and do not risk high investments in it. [ABSTRACT FROM AUTHOR]

Vandalism, the malicious modification of articles, is a serious problem for open access encyclopedias such as Wikipedia. The use of counter-vandalism bots is changing the way Wikipedia identifies and bans vandals, but their contributions are often not considered nor discussed. In this paper, we propose novel text features capturing the invariants of vandalism across five languages to learn and compare the contributions of bots and users in the task of identifying vandalism. We construct computationally efficient features that highlight the contributions of bots and users, and generalize across languages. We evaluate our proposed features through classification performance on revisions of five Wikipedia languages, totaling over 500 million revisions of over nine million articles. As a comparison, we evaluate these features on the small PAN Wikipedia vandalism data sets, used by previous research, which contain approximately 62,000 revisions. We show differences in the performance of our features on the PAN and the full Wikipedia data set. With the appropriate text features, vandalism bots can be effective across different languages while learning from only one language. Our ultimate aim is to build the next generation of vandalism detection bots based on machine learning approaches that can work effectively across many languages. [ABSTRACT FROM PUBLISHER]

Twitter has attracted millions of users to share and disseminate most up-to-date information, resulting in large volumes of data produced everyday. However, many applications in Information Retrieval (IR) and Natural Language Processing (NLP) suffer severely from the noisy and short nature of tweets. In this paper, we propose a novel framework for tweet segmentation in a batch mode, called HybridSeg. By splitting tweets into meaningful segments, the semantic or context information is well preserved and easily extracted by the downstream applications. HybridSeg finds the optimal segmentation of a tweet by maximizing the sum of the stickiness scores of its candidate segments. The stickiness score considers the probability of a segment being a phrase in English (i.e., global context) and the probability of a segment being a phrase within the batch of tweets (i.e., local context). For the latter, we propose and evaluate two models to derive local context by considering the linguistic features and term-dependency in a batch of tweets, respectively. HybridSeg is also designed to iteratively learn from confident segments as pseudo feedback. Experiments on two tweet data sets show that tweet segmentation quality is significantly improved by learning both global and local contexts compared with using global context alone. Through analysis and comparison, we show that local linguistic features are more reliable for learning local context compared with term-dependency. As an application, we show that high accuracy is achieved in named entity recognition by applying segment-based part-of-speech (POS) tagging. [ABSTRACT FROM PUBLISHER]

This paper provides the results of the case study conducted on a sample of 17 websites that identify themselves as e-book aggregators, five platforms for content publishing and 16 websites that present themselves as e-book distributors. While conducting the case study, the answers were sought to the questions about location of website, its owners, activities, distribution channels, services, partners, languages, content protection, scope of activities, number of authors and books, publishing areas, formats, etc. Based on the case studies, the results presented focus on the geographical distribution of the analyzed companies, distribution of companies according to the year in which they were established, distribution of companies by activity, the number of different input formats supported by aggregation companies, a separate service of conversion, output formats supported by aggregation companies, distribution on platforms and in bookstores, content protection options, possibilities of editing content in the cloud, models of payment for services, and other identified services. Based on the results of the study, a conclusion is made that e-book aggregation as a business model exists and that its further development will show the extent to which it is sustainable. [ABSTRACT FROM AUTHOR]

It is nowadays well-established that the construction of quality domain ontologies benefits from the involvement in the modelling process of more actors, possibly having different roles and skills. To be effective, the collaboration between these actors has to be fostered, enabling each of them to actively and readily participate to the development of the ontology, favoring as much as possible the direct involvement of the domain experts in the authoring activities. Recent works have shown that ontology modelling tools based on wikis’ paradigm and technology could contribute in meeting these collaborative requirements. This paper investigates, both at the theoretical and empirical level, the effectiveness of wiki features for collaborative ontology authoring in supporting teamworks composed of domain experts and knowledge engineers, as well as their impact on the entire process of collaborative ontology modelling and entity lifecycle. [ABSTRACT FROM AUTHOR]

Publishing manuscripts is the only way by which scientists communicate with each other. In recent times, there is an increasing desire to publish manuscripts from the developing world for a variety of reasons. Though, performing a research study is challenging in itself, writing it for publication is the final frontier that can be daunting, especially for the novice. Work that remains unpublished in one form or the other is essentially incomplete or undone. Hence, it is critically important for one to publish one's findings in a reputed journal. The purpose of this paper is to alleviate the mystique involved in manuscript writing and provide a blueprint where the subheadings given under each of the sections of introduction, methods, results and discussion can be expanded as per the particular study and the manuscript can be constructed in a stepwise manner. We hope that by following this approach, potential researchers and practicing ophthalmologists will develop the skill and aptitude for medical writing, and that the developing world shall do justice to its tremendous intellectual capital by making meaningful contributions to global scientific literature. [ABSTRACT FROM AUTHOR]

Open access spurred by the Internet has brought in new vistas for dissemination of scholarly content in almost all the disciplines. It has enabled agencies, publishers and individuals to distribute scholarly content online, free from licensing restrictions and cost. Like other fields, the growth of open access has also benefited the field of library and information science (LIS). In this paper an attempt has been made to assess the current status of open access journals in LIS covered in Directory of Open Access Journals (DOAJ) based on various parameters. [ABSTRACT FROM AUTHOR]

The author discusses the transition of "The International Journal of Occupational and Environmental Medicine" (IJOEM) from print to digital format. One of the reasons why several journals switched from paper-based to online-only publishing is to avoid the space limitations in the print edition. IJOEM decided to lower the number of hardcopies of The IJOEM to 500 per issue. The mean number of hits per month received by The IJOEM web site since January 2010 is shown.

The article provides issue information, which includes list of editors in chief for the periodical published by the organization IEEE Transactions on Microwave Theory & Techniques, which includes contact details of Luca Perregrini, information for authors, and the rules of submitting paper in electronic form such as size of the electronic file, website address where the paper is to be uploaded, and charges for submission.

The author offers insights on the decline of paper-based or physical scholarly publishing. He relates his own career which began in the print-on-paper publishing industry, the transformation into a digital publishing environment and the loss of societies' market share to commercial publishers before digitization.

An editorial is presented, in which the author discusses various changes to be adopted by the periodical. It mentions African Journal of Ecology encourages authors to share the data and other artifacts supporting the results in the paper by archiving it in an appropriate public repository. it also mentions plan of changing print publication to digital publishing.

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM PUBLISHER]