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Amazon's Kindle is one of many e-book readers currently available to the public. These e-book readers implement an electrophoretic display or e-paper technology which may have ramifications for libraries and publishing. Due to its low energy consumption, low heat production, and thin and portable form factor, e-paper stands to revolutionize how we access and consume information. [ABSTRACT FROM AUTHOR]

Electronic distribution is challenging the newspaper industry to seek new ways of publishing; consequently, news content could be processed on and for a variety of output platforms. Electronic paper (e-paper) could turn into a major newspaper publishing channel due to its ability to display content in a paper-like manner, with lower weight, lower power consumption, and facilitated handling compared to a computer, but without the major publishing and distribution costs associated with printed newspapers. This work is based on seven case studies of newspaper companies in Sweden, Europe and North America, and analyses newspaper companies' views on future e-paper publishing. The objective has been to examine the conditions that would enable the e-paper medium to become viable as a newspaper-publishing channel. Newspaper companies regard the idea of a future e-paper edition as very promising, but are uncertain as to what strategy to use. The final product will be a balance between cost, reorganization, the available number of rich media, and updates. Based on the companies' views, five models of how to incorporate an e-paper publishing channel into existing newspaper production have been proposed. The appropriateness of the models depends on each newspaper company's conditions, including assets, consumer base and demographics, current workflow, and future strategies. [ABSTRACT FROM AUTHOR]

This study seeks to assess the extent to which die digital book market is structuring independently from the print edition market by comparing the pricing of 559 digital and print French and American bestsellers during 2011. Two pricing methods are distinguished: "homothetic pricing," where the digital pricing is a reflection of the print pricing, and "heterothetic pricing," where the digital price is set according to new rules. The French and American markets do not have the same propensity to overcome the pricing practices in the print book market: While the French market's e-book structure is mirroring that of the print book industry, die American market tends to be more independent. This can be explained by die significant structural, legal, and institutional differences between the publishing industries of both countries. In addition, some factors favor die "heterothetic" pricing method: the number of pages and the type of book influence the degree of differentiation between print and digital prices of the same title [ABSTRACT FROM AUTHOR]

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]

Attempts to answer the question of who should own scientific papers. History of scientific publishing; How electronic communication has effected ways in which results are distributed; The assertion that scientists, administrators, and federal science policymakers must reconsider how results of publicly-funded research are best disseminated; Mentions the United States Copyright Act of 1976; Matching scientific research goals to public policy goals; Articulating the public benefits of research publication.

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]

Reports on efforts to create a web-based repository of biomedical information which will be hosted by the United States National Institutes of Health (NIH). Details of E-biosci; Use of previously reviewed articles; Questions regarding what benefits publishers will see from contributing to the site; Publications which may contribute such as `Molecular Biology of the Cell'; Involvement of Donald Varmus, NIH director.

The article presents a call for papers to be published in the Internet journal.

Reports that a group of researchers say they will stop buying, publishing, or reviewing for any scientific journal that refuses to place its research papers in a proposed online database, Public Library of Science, within six months of initial publication. Reaction of publishers, who claim that free access will leave journals without enough revenue to support peer review; Speculation that the research will end up on the publicly-funded PubMedCentral rather than on a private site.

The article provides information on the accomplishments of "ECS Transactions" (ECST), an online publication of the Electrochemical Society (ECS). It states that as of March 2009, ECST has published its 5,000th article on the society's conferences. It mentions that the advent of the electronic publication has contributed to the increased production. It adds that ECST has generated acclaims from students and researches. It adds that the publication will continue to pursue quality services.

The article reports on the new law which requires grantees of the National Institute of Health (NIH) to publish their biomedical manuscripts in the U.S. To comply with the new law, NIH informed its grantees to begin sending copies of their accepted, peer-reviewed manuscripts to NIH for posting in a free online archive. NIH warns grantees that failure to send the copies of their manuscripts could delay a grant or jeopardize new research funding. This public-access law is designed to enable taxpayers to learn about research they fund as a part of a spending bill Congress passed in December 2007.

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]

The article reports on the online publishing planning of physics journals by the American Physical Society (APS). APS has reported that it will be making full-text articles available free to read for all who will pay easy one-time fee. It recently announced that it will be charging a per article fee of $975 for its journal "Physical Review" and $1300 for "Physical Review Letters."

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]