Search

In a conventional library the librarian eliminates individual differences in concepts in queries and maintains the reliability of information. In a digital library, however, the goal is to not involve people, and so queries which eliminate precision problems in query results are in demand as a replacement for the librarian. In current retrieval systems, precision is improved by using a hierarchical method such as synonym notation processing. In methods based on word systems, processing to handle the inadequate expression of the intention of a query or the semantic interpretation of a query are insufficient, and information retrieval from a more hierarchical perspective is needed. In this paper the authors propose a retrieval method using a hierarchical perspective based on a system of concepts, and not a retrieval method based on conventional word systems. By adopting the EDR electronic dictionary as a thesaurus and using concept information, queries and words which appear in papers are not processed merely as character strings, but are used in queries with consideration for the meaning of the words. The authors' method can estimate imprecise information in the intentions of queries and the meaning hidden in words, allowing for appropriate query results to be provided to users without the cooperation of a librarian. © 2001 Scripta Technica, Syst Comp Jpn, 32(8): 40–52, 2001 [ABSTRACT FROM AUTHOR]

Purpose – In editorial peer review systems of journals, one does not always accept the best papers. Due to different human perceptions, the evaluation of papers by peer review (for a journal) can be different from the impact that a paper has after its publication (measured by number of citations received) in this or another journal. This system (and corresponding problems) is similar to the information retrieval process in a documentary system. Also there, one retrieves not always the most relevant documents for a certain topic. This is so because the topic is described in the command language of the documentary system and this command does not always completely cover the "real topic" that one wants to describe. This paper aims to address this issue. Design/methodology/approach – Based on this statement classical information retrieval evaluation techniques were applied to the evaluation of peer review systems. Basic in such an information retrieval evaluation are the notions of precision and recall and the precision-recall-curve. Such notions are introduced here for the evaluation of peer review systems. Findings – The analogues of precision and recall are defined and their curve constructed based on peer review data from the journal Angewandte Chemie – International Edition and on citation impact data of accepted papers by this journal or rejected but published elsewhere papers. It is concluded that, due to the imperfect peer review process (based on human evaluation), if we want to publish a high amount of qualified papers (the ones we seek), several non-qualified papers should also be accepted. Originality/value – The authors conclude that, due to the imperfect peer review process (based on human evaluation), if we want to publish a high amount of qualified papers (the ones we seek), one will also accept several non-qualified papers. [ABSTRACT FROM AUTHOR]

During the last two decades, a systematic re-examination of the whole information science field has taken place around the FIS--Foundations of Information Science--initiative. With the occasion of its Fourth Conference in Beijing 2010, a group of selected contributors and leading practitioners of those fields have been invited to contribute to this Special Issue. What is the status of information science today? What is the relationship between information and the laws of nature? Is information merely "physical"? What is the difference between information and computation? Has the genomic revolution changed the contemporary views on information and life? And what about the nature of social information? Cogent answers to these questions and to quite many others are attempted in the contributions that follow. [ABSTRACT FROM AUTHOR]

The need for academic researchers to retrieve patents and research papers is increasing, because applying for patents is now considered an important research activity. However, retrieving patents using keywords is a laborious task for researchers, because the terms used in patents for the purpose of enlarging the scope of the claims are generally more abstract than those used in research papers. Therefore, we have constructed a framework that facilitates patent retrieval for researchers, and have integrated research papers and patents by analysing the citation relationships between them. We obtained cited research papers in patents using two steps: (1) detection of sentences containing bibliographic information, and (2) extraction of bibliographic information from those sentences. To investigate the effectiveness of our method, we conducted two experiments. In the experiment involving Step 1, we prepared 42,073 sentences, among which a human subject manually identified 1,476 sentences containing citations of papers. For Step 2, we prepared 3,000 sentences, in which the titles, authors, and other bibliographic information were manually identified. We obtained a precision of 91.6%, and a recall of 86.9% in Step 1, and a precision of 86.2% and a recall of 85.1% in Step 2. Finally, we constructed an information retrieval system that provided two methods of retrieving research papers and patents. One method was retrieval by query, and another was from the citation relationships between research papers and patents. [ABSTRACT FROM AUTHOR]

Information retrieval (IR) is a science of searching for information. A query is used to extract information from database where fast query processing is the main issue. The mechanisms like index and hash table can be used to solve this problem but the main challenge is to find a proper index which improves query performance. This paper describes various indexing and hashing techniques in terms of query support, structure and application. B-tree, B+-tree, bitmap index are discussed for point query followed by spatial indexing techniques like quad tree, k-d tree, R-tree, R+-tree, R*-tree for range query and multidimensional data. [ABSTRACT FROM AUTHOR]

Similarity measure is calculated based on the syntactical representation of terms. Similarity measure used in data mining task likes clustering, and classification returns irrelevant information. The semantic similarity calculated based on the relatedness between wordpairs of terms returns better result. Many researchers proposed approaches for getting word similarity by using different sources like ontologies, thesauri etc. This Paper provides an overview of six existing semantic similarity measures and compared those semantic similarity measures using the wordpairs of sports domain ontology. This paper describes about how WordNet is used to retrieve the synonyms and using synsets how semantic similarity measures are calculated. Finally, comparison of selected semantic similarity measures for the given wordpairs with respect to the considered knowledge base domain ontology and WordNet is presented. [ABSTRACT FROM AUTHOR]

Objective: In 2002, the National Library of Medicine (NLM) introduced semi-automated indexing of Medline using the Medical Text Indexer (MTI). In 2021, NLM announced that it would fully automate its indexing in Medline with an improved MTI by mid-2022. This pilot study examines indexing using a sample of records in Medline from 2000, and how an early, public version of MTI's outputs compares to records created by human indexers. Methods: This pilot study examines twenty Medline records from 2000, a year before the MTI was introduced as a MeSH term recommender. We identified twenty higher- and lower-impact biomedical journals based on Journal Impact Factor (JIF) and examined the indexing of papers by feeding their PubMed records into the Interactive MTI tool. Results: In the sample, we found key differences between automated and human-indexed Medline records: MTI assigned more terms and used them more accurately for citations in the higher JIF group, and MTI tended to rank the Male check tag more highly than the Female check tag and to omit Aged check tags. Sometimes MTI chose more specific terms than human indexers but was inconsistent in applying specificity principles. Conclusion: NLM's transition to fully automated indexing of the biomedical literature could introduce or perpetuate inconsistencies and biases in Medline. Librarians and searchers should assess changes to index terms, and their impact on PubMed's mapping features for a range of topics. Future research should evaluate automated indexing as it pertains to finding clinical information effectively, and in performing systematic searches. [ABSTRACT FROM AUTHOR]

On account of prevalence of mobile devices, a variety of mobile-based services have been conducted recently. In this situation, it is possible to serve the information that fits to users' requests according to the users' context using mobile devices. Therefore, it is necessary to research data mining techniques with mobile devices. Therefore, we researched information retrieval system in mobile environment. We applied semantic data mining method with context information ontology. These techniques of semantic information retrieval can provide the information according to users' context information such as location, weather, user preference etc. exactly and rapidly anytime and anyplace. In modern society, it is essential to develop mobile information retrieval system which is efficient to users. Also, the system can provide users' current location and the location information with Google map APIs in mobile devices. Therefore, in this paper, we researched semantic data mining technique with context information ontology using mobile techniques. And we compared and evaluated our proposed model and the existing model in three areas and showed our proposed model has higher performance. [ABSTRACT FROM AUTHOR]

The Information Retrieval user experience has remained largely unchanged since its inception for computers and mobile devices alike. However, recent developments in Virtual Reality hardware (pioneered by Oculus Rift in 2013) could introduce a new environment for Information Retrieval. This paper reports the results of a Scoping Literature Review (PRISMA-ScR) by rigorously examining the entire body of relevant literature with reproducible methods. The following research questions are answered: "What prototypes and concepts of Virtual Reality Information Retrieval systems with current generation hardware exist?", "How are user interaction and especially user input realised in these systems?", "What Retrieval features are used in these systems?", "How are search results displayed in these systems?" and "Can these VR IR systems compare to traditional (non-VR) IR systems?". After querying Google Scholar, Scopus and Web of Science, 1042 documents were reviewed in depth. Key features and attributes of the systems are summarised and discussed. Sketches of the user interfaces are included as well. The 30 documents that were relevant to the research questions include 16 distinct systems or theories. They discuss and utilise several user input technologies, ranging from controllers, voice input or hand tracking. Although conventional retrieval features are less common, systems enable retrieval of literature, 3D objects, images, books and texts and arrange them in a virtual space (e.g. as grids, arcs or maps). Finally, many of these systems were compared to conventional counterparts through user evaluation (n = 10). Most found user task times to be shorter or equal (n = 5, n = 3). In the seven papers that measured user performance (rate of correct solutions), three reported better performance (one equal). Notably, users always were more satisfied with the Virtual Reality systems compared to conventional ones. Possible limitations of these evaluations are demographic selection and the quality of baseline systems (control). [ABSTRACT FROM AUTHOR]

Unsurprisingly, the web has become a standard resource to access information. Universities and organizations have significantly switched their attention towards web-based information systems. It is challenging to design an Information Retrieval (IR) system which can search relevant information and ensure both high usability and user satisfaction. High usability results in reduced usage time, eliminated frustrations and increased satisfaction. Because the IR websites differ in technical characteristics and scope, it is also challenging to design and conduct the usability tests of these systems. Previous studies examining the usability of IR websites have researched a limited number of IR websites and/or based their analysis on a review of the search criteria and search results, and thes studies have addressed quality and accuracy of the search results. This paper provides a much-needed overview of popular academic IR websites from a usability perspective. We compared different design styles and layouts of popular IR websites. By employing usability testing and SUS techniques, the perceived difficulty has been analyzed, while users perform the given tasks. Our test results assert that no matter how accurate an IR system is, users might find it difficult or impossible to utilize if it is not usable. [ABSTRACT FROM AUTHOR]

Background: Information specialists conducting searches for systematic reviews need to consider key questions around which and how many sources to search. This is particularly important for public health topics where evidence may be found in diverse sources. Objectives: The objective of this review is to give an overview of recent studies on information retrieval guidance and methods that could be applied to public health evidence and used to guide future searches. Methods: A literature search was performed in core databases and supplemented by browsing health information journals and citation searching. Results were sifted and reviewed. Results: Seventy‐two papers were found and grouped into themes covering sources and search techniques. Public health topics were poorly covered in this literature. Discussion: Many researchers follow the recommendations to search multiple databases. The review topic influences decisions about sources. Additional sources covering grey literature eliminate bias but are time‐consuming and difficult to search systematically. Public health searching is complex, often requiring searches in multidisciplinary sources and using additional methods. Conclusions: Search planning is advisable to enable decisions about which and how many sources to search. This could improve with more work on modelling search scenarios, particularly in public health topics, to examine where publications were found and guide future research. [ABSTRACT FROM AUTHOR]

This paper examines the decision points over the course of ten years of development of an institutional repository. Specifically, the focus is on the impact and influence from the open-source community, the needs of the local institution, the role that team dynamics plays, and the chosen platform. Frequently, the discussion revolves around the technology stack and its limitations and capabilities. Inherently, any technology will have several features and limitations, and these are important in determining a solution that will work for your institution. However, the people running the system and developing the software, and their enthusiasm to continue work within the existing software environment in order to provide features for your campus and the larger open-source community, will play a bigger role than the technical platform. These lenses are analyzed through three points in time: the initial roll out of our institutional repository, our long-term running and maintenance, and eventual new development and why we made the decisions we made at each of those points in time. [ABSTRACT FROM AUTHOR]

With the development of information technologies, more and more information retrieval tools, containing a wide variety of information, can be found. Internet resources, universal and specialized search engines, virtual libraries are becoming the main information retrieval tools for students. The article introduces an exploratory (pilot) research aiming to find out the differences of information retrieval between Lithuanian and Portuguese students. Šiauliai State College offers a unique study programme Information Management, having a signed contract of a double diploma with Porto (Portugal) Polytechnic Institute Porto Accounting and Business School (ISCAP). 10 Portuguese and 10 Lithuanian students participated in the research. The online questionnaire was forwarded to the students of ISCAP Porto Accounting and Business School and to the second year students of the study programme of Information Management at Šiauliai State College. The research revealed that the respondents Lithuanian students look for scientific papers and books, whereas Portuguese students search for basic information and scientific papers. All the respondents of the survey identified Google Scholar as the most important search engine for scientific information retrieval. [ABSTRACT FROM AUTHOR]

The article reports that British manufacturer of aircrete building products H+H UK Ltd., says it is waging war on the paper documents. The company has eliminated many thousands of paper documents after installing Version One's document storage and form production software. The company is planning to eradicate all unnecessary paper document across the company. According to Brian Collins, manager of the company, the company archived documents by microfiche which was a slow and archaic process. Version One's electronic storage technology DbArchive and electronic form production technology DbForm are two solutions for the company to solve the problem.

Purpose - Entering data about published research results should be implemented as a web application that enables authors to input their own data without the knowledge of the bibliographic standard. The aim of this research is to develop a research management system based on a bibliographic standard and to provide data exchange with other research management systems based on the Common European Research Information Format (CERIF) data model. Design/methodology/approach - Object-oriented methodology was used for information system modelling. The modelling was carried out using the computer-aided software engineering (CASE) tool that supports the Unified Modelling Language 2.0 (UML 2.0). The implementation was realised using a set of open-source solutions written in Java. Findings - The result is a system for managing data about published research results. The main system features are the following: public access via the web; authors input data about their own publications by themselves; data about publications are stored in the MARC 21 format; and the user interface enables authors to input data without the knowledge of the MARC 21 format. Research limitations/implications - A method of verifying accuracy of entered data has not been considered yet. It is necessary to allow authorised persons to verify the accuracy of the data. After verifying the accuracy the authors cannot change the data. Practical implications - This software system has been verified and tested on data about published results of researchers employed at the University of Novi Sad in Serbia. This system can be used for evaluation and reporting on scientific research results, generating bibliographies of researchers, research groups and institutions etc. Originality/value - A part of the research management system for entering data about authors and published results is implemented. Data about publications are stored in a bibliographic format and authors can input data about their own publications without the knowledge of the bibliographic standard. The main feature of the system architecture is mutual independence of the component for interaction with users and the component for persisting and retrieving data from the bibliographic records database. [ABSTRACT FROM AUTHOR]

Discussions relating to the identification of courses and the development of curricula for the information- science field cannot yield meaningful results unless the conceptual framework of the field is first delimited and its basic segments defined. Starting with the current ASIS definition of information science, an analysis is made of the rationale of current thinking relevant to the conceptual boundaries and intellectual content of the field. Information science is analyzed to be comprised of the segments of: (1) Conceptualization, (2) Storage/Transmission, and (3) Utilization. Two of the segments are shown to be based on subjective notions, which can be investigated, for the most part, through the employment of statistical and normative survey methodology. One of the segments is shown to be susceptible of the application of more rigorous research methodology capable of yielding empirical proof. Since all three segments form integral parts of the field, they need to be fully represented in the information science curriculum. The technologist as well as the humanist can make significant contributions to the growth and development of the information-science field. [ABSTRACT FROM AUTHOR]

In the biomedical field due to tremendous medical research, every year the medical papers generated is very huge. In order to process these tremendous amounts of textual data, the information retrieval techniques are combined with machine learning methods like natural language processing (NLP) for finding the useful insights in data for NLP tasks. In this work, we have addressed the challenges involved in existing NLP techniques like Word2Vec, Doc2Vec, and Biosent2Vec and followed by the traditional classification of articles with Concept2Vec and random forest classification. Concept vector techniques are emerging methods in NLP and in information retrieval systems. Pretrained concept encoders are available in Machine learning, whereas no such exists in biomedical domain. In this paper a proposal on Concept2Vec trained from biomedical text is highlighted. Our work accurately emphasizes on the quality of semantics defined between the medical terms, which can help the medical practitioners in taking errorless decisions. In this work 20 thousand biomedical documents are considered for Concept2Vec embeddings and the proposed approach have shown best concept similarity in terms of relevant measures compared with existing approaches such as Word2Vec, global vectors (GloVe), fastText, and BioSentVec, bidirectional encoder representations from transformers (BERT), biomedical-BERT. [ABSTRACT FROM AUTHOR]

The process of data analytics on large-scale government administrative data — that belong to various domains like education, transport, energy, and health — can be enhanced by retrieving pertinent documents from diverse data sources. Without a supporting framework of metadata, big data analytics can be daunting. Even though statistical algorithms can perform extensive analyses on a variety of data with little help from metadata, applying these techniques to heterogeneous data may not always result in reliable findings. Recently, semantics-aware (or semantic search) search techniques received much attention as they utilize implicit knowledge to enhance the search. Similarly, traditional search engines rely on the inherent linkages within the underlying data model to improve their search quality. In the case of general-purpose information retrieval systems, to gather information from the internet (open access data) or to access open government administrative data, a domain agnostic ontology shall be employed to supply background knowledge. This paper draws on research undertaken by the authors at IIIT Bangalore Center for Open Data Research (CODR) in developing a semantics-aware data lake framework to host and analyze government administrative data. In this study, we present an ontology-based document retrieval solution where an ontology serves as an intermediary to close the gap between what the user seeks and what the search retrieves. Although our study settings are based on the Government of Karnataka (GoK, India), we believe the findings have wider resonance. Our experimental results based on agricultural data from the GoK look promising. [ABSTRACT FROM AUTHOR]

The article introduces various topics covered in the issue including benefits of using sequence representations in medical field, the effectiveness of the retrieval-given queries, and major improvements in template extraction post temporality classifications.

Implementation of ocean observation sensors are booming in recent years for encouraging research among coastal areas all over the world. This results in a copious amount of big data which makes it difficult for traditional data processing applications to manage them. The complexity in ocean observing community is heterogeneity and interpretation, which directs to a high-end information retrieval system. World Wide Web Consortium (W3C) spreads the usage of Semantic Web (SW) that provide easier way to search, reuse, combine and share information by integrating the data into a single platform. The use of semantic web in big data management helps to increase end-users ability for self-management of data from various sources, to handle the concepts and relationships of a domain and to manage the terminologies while connecting data from a varied data sources. This paper focuses on integrating big data with semantic web technology by developing a knowledge base system through ontology to solve the problem of heterogeneity in ocean observing communities. Ontology refers to a set of machine-readable controlled vocabularies which interprets big data by combining the data concepts with ontology classes. The proposed data model upgrades the information system in terms of improvising data analysis, discovery, retrieval and decision making. In addition to that, this paper also evaluates the quality of proposed ontology and found to be 39.28% improved in completeness, 45.29% reduced in structural complexity, 11% and 37.7% decreased in conciseness and correctness, respectively. [ABSTRACT FROM AUTHOR]

Information retrieval aims to retrieve the documents that answer users' queries. A typical search process consists of different phases for which a variety of components have been defined in the literature; each one having a set of hyper-parameters to tune. Different studies focused on how and how much the components and their hyper-parameters affect the system performance in terms of effectiveness, others on the query factor. The aim of these studies is to better understand information retrieval system effectiveness. This paper reviews the literature of this domain. It depicts how data analytics has been used in IR for a better understanding system effectiveness. This review concludes lack of full understanding of system effectiveness according to the context although it has been possible to adapted the query processing to some contexts successfully. This review also concludes that, even if it is possible to distinguish effective from non effective system on average on a query set, nor the system component analysis nor the query features analysis were successful in explaining when and why a particular system fails on a particular query. [ABSTRACT FROM AUTHOR]

Information transmission and storage have gained traction as unifying concepts to characterize biological systems and their chances of survival and evolution at multiple scales. Despite the potential for an information-based mathematical framework to offer new insights into life processes and ways to interact with and control them, the main legacy is that of Shannon's, where a purely syntactic characterization of information scores systems on the basis of their maximum information efficiency. The latter metrics seem not entirely suitable for biological systems, where transmission and storage of different pieces of information (carrying different semantics) can result in different chances of survival. Based on an abstract mathematical model able to capture the parameters and behaviors of a population of single-celled organisms whose survival is correlated to information retrieval from the environment, this paper explores the aforementioned disconnect between classical information theory and biology. In this paper, we present a model, specified as a computational state machine, which is then utilized in a simulation framework constructed specifically to reveal emergence of a "subjective information", i.e., trade-off between a living system's capability to maximize the acquisition of information from the environment, and the maximization of its growth and survival over time. Simulations clearly show that a strategy that maximizes information efficiency results in a lower growth rate with respect to the strategy that gains less information but contains a higher meaning for survival. [ABSTRACT FROM AUTHOR]

Research patterns could enhance understanding of the Information Systems (IS) field. Citation analysis is the methodology commonly used to determine such research patterns. In this study, the citation methodology is applied to one of the top-ranked Information Systems conferences—International Conference on Information Systems (ICIS). Information is extracted from papers in the proceedings of ICIS 2000 to 2002. A total of 145 base articles and 4,226 citations are used. Research patterns are obtained using total citations, citations per journal or conference, and overlapping citations. We then provide the citation ranking of journals and conferences. We also examine the difference between the citation ranking in this study and the ranking of IS journals and IS conferences in other studies. Based on the comparison, we confirm that IS research is a multidisciplinary research area. We also identify the most cited papers and authors in the IS research area, and the organizations most active in producing papers in the top-rated IS conference. We discuss the findings and implications of the study. [ABSTRACT FROM AUTHOR]

Query, expressing the user need and requirement, has an important role, in an information retrieval system, for reaching a high accuracy search. In this paper, we present an overview of the different refinement operations that the query may undergo, in the sake to enhance performance of an information retrieval system, such as: automatic query formulation through words prevision, query reformulation, query expansion, and query optimization. [ABSTRACT FROM AUTHOR]

In this internet-based world where a large amount of information exists on the World Wide Web (WWW), the information retrieval systems are mainly centred on topic-based classification. Numerous efforts and time have been consumed for relevant information extraction through major search engines if the data is not organised correctly. Ontologies proved to be an effective technique for representing and retrieving information, which is the key idea in semantic web applications. Ontologies not only help in efficient knowledge representation and information retrieval, but it also helps in mapping the hidden knowledge about a subject. This paper discusses the process and method of building ontology on the "Energy access" domain. The methodology is based on the tools used in developing the ontology. Several tools are used to create an ontology. Protégé is a most popular tool for ontology editing and for developing ontology.1 In this paper, various aspects like super class and subclass hierarchy, creating a subclass, instances for class illustration, query retrieval process, visualisation, and graph views have been demonstrated by using protégé software. [ABSTRACT FROM AUTHOR]

The current practice of users searching for different types of geo-resources in a geographic area and wishing to identify the most convenient routes for visiting the most relevant ones, requires the iterative formulation of several queries: first to identify the more interesting resources and then to select the best route to visit them. In order to simplify this process, in this paper a novel functionality for a geographic information retrieval (GIR) system is proposed, which retrieves and ranks several routes for visiting a number of relevant georeferenced resources as a result of a single query, named flexible trip-planning query. An original retrieval model is defined to identify the relevant resources and to rank the most convenient routes by taking into account personal user preferences. To this end, a graph-based algorithm is defined, exploiting prioritized aggregation to optimize the routes' identification and ranking. The proposed algorithm is applied in the proof-of-concept of a Smart cOmmunity-based Geographic infoRmation rEtrievAl SysTem (SO-GREAT) designed to strengthen local communities: it collects and manages open data from regional authorities describing categories of authoritative territorial resources and services, such as schools, hospitals, etc., and from volunteered geographic services (VGSs) created by citizens to offer services in their neighbourhood. [ABSTRACT FROM AUTHOR]

This research proposes a new approach to improve information retrieval systems based on a multinomial naive Bayes classifier (MNBC), Bayesian networks (BNs), and a multi-terminology which includes MeSH thesaurus (Medical Subject Headings) and SNOMED CT (Systematized Nomenclature of Medicine of Clinical Terms). Our approach, which is entitled improving semantic information retrieval (IMSIR), extracts and disambiguates concepts and retrieves documents. Relevant concepts of ambiguous terms were selected using probability measures and biomedical terminologies. Concepts are also extracted using an MNBC. The UMLS (Unified Medical Language System) thesaurus was then used to filter and rank concepts. Finally, we exploited a Bayesian network to match documents and queries using a conceptual representation. Our main contribution in this paper is to combine a supervised method (MNBC) and an unsupervised method (BN) to extract concepts from documents and queries. We also propose filtering the extracted concepts in order to keep relevant ones. Experiments of IMSIR using the two corpora, the OHSUMED corpus and the Clinical Trial (CT) corpus, were interesting because their results outperformed those of the baseline: the P@50 improvement rate was +36.5% over the baseline when the CT corpus was used. [ABSTRACT FROM AUTHOR]

Summary: Data reliability is the main part of the intelligence of current information systems. Objects can change their status anytime, highlighting the validity frame. Several solutions and architectures have been developed in the recent past to cover the complexity of data management over the whole life cycle. The common and most significant aspect is just the validity and correctness of the stored data tuples. Solutions, where data were updated always synchronously in strictly defined time points, frequency, and granularity, are over. Therefore, it is inevitable to create a solution suitable for the particular system to reach the best performance. We reference an attribute‐oriented temporal model with reflection on data grouping technologies. Many times, there is a case, during which the object is defined only partially or data tuple is not present at all. For these reasons, undefined values must be stored in the database in the form of time itself or attribute expressing the state of the object. This paper deals with time‐oriented database architectures, manages undefined values, and proposes a complex system classification based on transactions, approaches, and indexes. It deals with techniques to model undefined values and covers synchronization processes using data groups. We propose solutions for effective data retrieval with an emphasis on undefined values and states. [ABSTRACT FROM AUTHOR]

One of the most common ways in which results are displayed by an information retrieval system is in the form of a list, in which the most relevant results appear in the first positions. Today's large screens, however, allow one to create more complex displays of results, especially in cases such as image retrieval, in which each unit returned is fairly compact. For these layouts the simple list model is no longer valid, since the relations between the slots in which the results are placed do not form a sequence, that is, the relation among them is no longer that of a total order. In this paper we model these layouts as partial orders and show that a “stalwart display” property (a layout in which items’ relevance is unambiguously conveyed by their display position) can be obtained only in the case of lists. For the other layouts, we define two classes of representation functions: “safe” functions (which display results without adding spurious structure) and “rich” functions (which do not drop any structure from the result set), as well as an algorithm to optimally display fully ordered result sets in arbitrary display layouts. [ABSTRACT FROM AUTHOR]

In this issue we introduce a new section of the Journal called Capsule Reviews. It is intended to provide a short succinct review of each paper in the issue, in order to bring the content to a wider readership. All reviews here are by Associate Editor, Fairouz Kamareddine. [ABSTRACT FROM PUBLISHER]

To implement the indexing in multilingual data set, the indexing process must know. This paper gives the brief about indexing and presents role of indexing, logical view of indexing, types of indexing, indexing process, data structure of indexing, representation of indexing and indexing framework. Indexing is an important concept to implement in retrieval process. By the indexing, retrieval process will reduce the time. The indexing part performs the complete article pool to shape index constructions that permit for resourceful search. These are typically inverted tables. Each article is so prepossessed and recorded to a vector demonstration. At the end indexing method is applied to the multilingual information retrieval system and shows the results. [ABSTRACT FROM AUTHOR]

Let us consider the following scenario: A human is working with a corpus of text documents. In this corpus, the human needs to know documents with similar content and highlight relevant locations in the retrieved documents. An information system displaying the contents of the corpus and providing an information retrieval agent will help the human. To perform information retrieval on the corpus, the agent used internally in the information system may need additional data associated with the documents. In order to support this, the so-called Subjective Content Descriptions (SCDs) provide additional location-specific data for text documents. SCDs are subjective in the sense that the agent associates data with sentences to reflect the beliefs of users. In our scenario, the agent needs SCDs referencing sentences of similar content across various documents in the corpus and most text documents are not associated with SCDs. Therefore, this paper presents UESM, the Unsupervised Estimator for SCD Matrices, an approach to associate any corpus with SCDs. In an evaluation, we show that the performance of UESM in estimating topics of similar content in the corpus is on par with Latent Dirichlet Allocation, while UESM provides the SCDs referencing sentences of similar content. [ABSTRACT FROM AUTHOR]

This paper presents ARCA, a software system that enables semantic search and exploration over a book catalog. The main purpose of this work is twofold: to propose a general paradigm for a semantic enrichment workflow and to evaluate a visual approach to information retrieval based on extracted information and existing knowledge graphs. ARCA has been designed and implemented following a user-centered design approach. Two different releases of the system have incrementally and iteratively developed and evaluated. The first release has evaluated the quality and usefulness of the extracted data. The second release, whose design was a refinement based on the previous evaluation results, was assessed by several users. Moreover, a comparative test with other information retrieval systems was conducted in order to study the potential added-value of the system. ARCA is employed in a real editorial scenario to visually search and explore the books of a publishing house. [ABSTRACT FROM AUTHOR]

The analysis of the information retrieval system focuses on the notion of appropriate and irrelevant documents. The performance predictor, including accuracy and reminder, is used to establish how well the device satisfies consumer requirements. The effectiveness of the indexing and retrieval is calculated by contrasting a typical collection of queries and documents with the efficacy, functionality, and systemic approach. Important evaluations are used to measure functionality, performance (precession and retraction), compilation, and interface assessments. Document and query indexing, query assessment, and system assessment are key issues in information retrieval. This paper uses the human–computer interaction based on the intelligent information retrieval method (HCI-IRM). The proposed method concentrates on customer satisfaction, the main success assessment metric. It identifies the collection of related records at a given time within the collection. An information retrieval system's main objective is to obtain the information. It is either the actual information or the documents containing the information substitutes which completely or partly correspond to the customer's query evaluation. The extraction and recruitment of knowledge-based data from a database are usually related to the retrieval of information. The retrieval and precise technology are used to assess the efficiency of the data recovery system framework. As a result, HCI-IRM enhances the response time, and the relevance of the outcomes is key to customer satisfaction. Comparison of Yahoo and Google search engines focused on accuracy and reminder technology. [ABSTRACT FROM AUTHOR]

Query expansion is an important approach utilized to improve the efficiency of data retrieval tasks. Numerous works are carried out by the researchers to generate fair constructive results; however, they do not provide acceptable results for all kinds of queries particularly phrase and individual queries. The utilization of identical data sources and weighting strategies for expanding such terms are the major cause of this issue which leads the model unable to capture the comprehensive relationship between the query terms. In order to tackle this issue, we developed a novel approach for query expansion technique to analyze the different data sources namely WordNet, Wikipedia, and Text REtrieval Conference. This paper presents an Improved Aquila Optimization-based COOT(IAOCOOT) algorithm for query expansion which retrieves the semantic aspects that match the query term. The semantic heterogeneity associated with document retrieval mainly impacts the relevance matching between the query and the document. The main cause of this issue is that the similarity among the words is not evaluated correctly. To overcome this problem, we are using a Modified Needleman Wunsch algorithm algorithm to deal with the problems of uncertainty, imprecision in the information retrieval process, and semantic ambiguity of indexed terms in both the local and global perspectives. The k most similar word is determined and returned from a candidate set through the top-k words selection technique and it is widely utilized in different tasks. The proposed IAOCOOT model is evaluated using different standard Information Retrieval performance metrics to compute the validity of the proposed work by comparing it with other state-of-art techniques. [ABSTRACT FROM AUTHOR]

Due to the tremendous use of computers, the need for dealing with digital information continues to grow. This has led to the need for constructing a structure for saving information in a way that eases data retrieval and processing. An information system is a table form that contains all the data needed for a user to reach a decision. Information systems are the most common form used for knowledge and data representation, and attribute reduction plays an important role in data processing. This paper is devoted to proposing a strategy for attributes reduction based on the similarity relation and pretopological concepts. Moreover, new types of pretopological spaces are to be constructed from the information system. Furthermore, a comparison between pretopologies and their pre-interiors constructed from the information system, as well as the different types of pretopological spaces, is investigated. Finally, the concept of the cover pretopology is applied to the information system. [ABSTRACT FROM AUTHOR]

Data structures and especially the relationship among the data entities have changed in the last couple of years. The network-like graph representations of data-model are becoming more and more common nowadays, since they are more suitable to depict these, than the well-established relational data-model. The graphs can describe large and complex networks — like social networks — but also capable of storing rich information about complex data. This was mostly of relational data-model trait before. This also can be achieved with the use of the knowledge representation tool called "hypergraphs". To utilize the possibilities of this model, we need a practical way to store and process hypergraphs. In this paper, we propose a way by which we can store hypergraphs model in the SAP HANA in-memory database system which has a "Graph Core" engine besides the relational data model. Graph Core has many graph algorithms by default however it is not capable to store or to work with hypergraphs neither are any of these algorithms specifically tailored for hypergraphs either. Hence in this paper, besides the case study of the two information systems, we also propose pseudo-code level algorithms to accommodate hypergraph semantics to process our IS model. [ABSTRACT FROM AUTHOR]

Bilingual corpora are an essential resource used to cross the language barrier in multilingual natural language processing tasks. Among bilingual corpora, comparable corpora have been the subject of many studies as they are both frequent and easily available. In this paper, we propose to make use of formal concept analysis to first construct concept vectors which can be used to enhance comparable corpora through clustering techniques. We then show how one can extract bilingual lexicons of improved quality from these enhanced corpora. We finally show that the bilingual lexicons obtained can complement existing bilingual dictionaries and improve cross-language information retrieval systems. [ABSTRACT FROM AUTHOR]