Search results

This paper evaluates the precision of four metasearch engines (MSEs) – DuckDuckGo, Dogpile, Metacrawler and Startpage, to determine which metasearch engine exhibits the highest level of precision and to identify the metasearch engine that is most likely to return the most relevant search results.

The research is divided into two parts: the first phase involves four queries categorized into two segments (4-Q-2-S), while the second phase includes six queries divided into three segments (6-Q-3-S). These queries vary in complexity, falling into three types: simple, phrase and complex. The precision, average precision and the presence of duplicates across all the evaluated metasearch engines are determined.

The study clearly demonstrated that Startpage returned the most relevant results and achieved the highest precision (0.98) among the four MSEs. Conversely, DuckDuckGo exhibited consistent performance across both phases of the study.

The study only evaluated four metasearch engines, which may not be representative of all available metasearch engines. Additionally, a limited number of queries were used, which may not be sufficient to generalize the findings to all types of queries.

The findings of this study can be valuable for accreditation agencies in managing duplicates, improving their search capabilities and obtaining more relevant and precise results. These findings can also assist users in selecting the best metasearch engine based on precision rather than interface.

The study is the first of its kind which evaluates the four metasearch engines. No similar study has been conducted in the past to measure the performance of metasearch engines.

The interpretation of any emerging form or period in art history was never a trivial task. However, in the case of digital art, technology, becoming an integral part, multiplied the complexity of describing, systematizing and evaluating it. This article investigates the most common metadata standards for the documentation of art as a broad category and suggests possible next steps toward an extended metadata standard for digital art.

Describing several techno-cultural phenomena formed in the last decade, manifesting the extendibility of digital art (its ability to be easily extended across multiple modalities), the article, at first, points to the long overdue need to re-evaluate the standards around it. Then it suggests a deeper analysis through a comparative study. In the scope of the study three artworks, The Arnolfini Portrait (Jan van Eyck), an iconic example of the early Renaissance, The World's First Collaborative Sentence (Douglas Davis), a classic example of early Internet art and Fake It Till You Make It (Maya Man), a prominent example of the blockchain art, are examined following the structure of the VRA Core 4.0 standard.

The comparative study demonstrates that digital art is more multi-semantic than traditional physical art, and requires new taxonomies as well as approaches for data acquisition.

Acknowledging that digital art simply has not yet evolved to the stage of being systematically collected by cultural institutions for documentation, curation and preservation, but otherwise, in the past few years, it has been at the front-center of social, economic and technological trends, the article suggests looking for hints on the future-proof extended metadata standard in some of those trends.

Develop a comprehensive framework for assessing the knowledge organization systems (KOSs), including the taxonomy of Wikipedia and the ontologies of Wikidata, with a specific focus on enhancing management and retrieval with a gender nonbinary perspective.

This study employs heuristic and inspection methods to assess Wikipedia’s KOS, ensuring compliance with international standards. It evaluates the efficiency of retrieving non-masculine gender-related articles using the Catalan Wikipedian category scheme, identifying limitations. Additionally, a novel assessment of Wikidata ontologies examines their structure and coverage of gender-related properties, comparing them to Wikipedia’s taxonomy for advantages and enhancements.

This study evaluates Wikipedia’s taxonomy and Wikidata’s ontologies, establishing evaluation criteria for gender-based categorization and exploring their structural effectiveness. The evaluation process suggests that Wikidata ontologies may offer a viable solution to address Wikipedia’s categorization challenges.

The assessment of Wikipedia categories (taxonomy) based on KOS standards leads to the conclusion that there is ample room for improvement, not only in matters concerning gender identity but also in the overall KOS to enhance search and retrieval for users. These findings bear relevance for the design of tools to support information retrieval on knowledge-rich websites, as they assist users in exploring topics and concepts.

Recent archiving and curatorial practices took advantage of the advancement in digital technologies, creating immersive and interactive experiences to emphasize the plurality of memory materials, encourage personalized sense-making and extract, manage and share the ever-growing surrounding knowledge. Audiovisual (AV) content, with its growing importance and popularity, is less explored on that end than texts and images. This paper examines the trend of datafication in AV archives and answers the critical question, “What to extract from AV materials and why?”.

This study roots in a comprehensive state-of-the-art review of digital methods and curatorial practices in AV archives. The thinking model for mapping AV archive data to purposes is based on pre-existing models for understanding multimedia content and metadata standards.

The thinking model connects AV content descriptors (data perspective) and purposes (curatorial perspective) and provides a theoretical map of how information extracted from AV archives should be fused and embedded for memory institutions. The model is constructed by looking into the three broad dimensions of audiovisual content – archival, affective and aesthetic, social and historical.

This paper contributes uniquely to the intersection of computational archives, audiovisual content and public sense-making experiences. It provides updates and insights to work towards datafied AV archives and cope with the increasing needs in the sense-making end using AV archives.

This study aims to explore the application of emojis to mood descriptions of fiction. The three goals are investigating whether Cho et al.'s model (2023) is a sound conceptual framework for implementing emojis and mood categories in information systems, mapping 30 mood categories to 115 face emojis and exploring and visualizing the relationships between mood categories based on emojis mapping.

An online survey was distributed to a US public university to recruit adult fiction readers. In total, 64 participants completed the survey.

The results show that the participants distinguished between the three families of fiction mood categories. The three families model is a promising option to improve mood descriptions for fiction. Through mapping emojis to 30 mood categories, the authors identified the most popular emojis for each category, analyzed the relationships between mood categories and examined participants' consensus on mapping.

This study focuses on applying emojis to fiction reading. Emojis were mapped to mood categories by fiction readers. Emoji mapping contributes to the understanding of the relationships between mood categories. Emojis, as graphic mood descriptors, have the potential to complement textual descriptors and enrich mood metadata for fiction.

Starting from the status quo, the paper outlines perspectives and challenges for the connection and interlinking of digitised and digital archival data. The following topics are addressed: Where are fields of action and what are the means of archives? Which functional and technical requirements are to be considered, and what is the role of portal infrastructures linking together various different institutions?

Considering needs of users and general framework conditions, the paper examines new approaches emerging in Germany. It outlines recent projects and considerations aiming to improve services and visibility of archives within the national data infrastructure in Germany.

Cross-connections are no new phenomenon, but change their appearance significantly in a digital context. In this respect, both smaller and bigger archives profit from participation in larger digital networks. Furthermore, archives need to keep in mind to reflect the quality of their digital (meta)data regularly and to offer or join systems that functionally and technically support cross-connection and interlinking of data.

The paper endeavours to show the importance of digital cross-connections and the role of portal infrastructures for visibility, online-distribution and use of digital archival metadata and data.

This study addresses the need for a theory-guided, rich, descriptive account of research data repositories' (RDRs) understanding of data quality and the structures of their data quality assurance (DQA) activities. Its findings can help develop operational DQA models and best practice guides and identify opportunities for innovation in the DQA activities.

The study analyzed 122 data repositories' applications for the Core Trustworthy Data Repositories, interview transcripts of 32 curators and repository managers and data curation-related webpages of their repository websites. The combined dataset represented 146 unique RDRs. The study was guided by a theoretical framework comprising activity theory and an information quality evaluation framework.

The study provided a theory-based examination of the DQA practices of RDRs summarized as a conceptual model. The authors identified three DQA activities: evaluation, intervention and communication and their structures, including activity motivations, roles played and mediating tools and rules and standards. When defining data quality, study participants went beyond the traditional definition of data quality and referenced seven facets of ethical and effective information systems in addition to data quality. Furthermore, the participants and RDRs referenced 13 dimensions in their DQA models. The study revealed that DQA activities were prioritized by data value, level of quality, available expertise, cost and funding incentives.

The study's findings can inform the design and construction of digital research data curation infrastructure components on university campuses that aim to provide access not just to big data but trustworthy data. Communities of practice focused on repositories and archives could consider adding FAIR operationalizations, extensions and metrics focused on data quality. The availability of such metrics and associated measurements can help reusers determine whether they can trust and reuse a particular dataset. The findings of this study can help to develop such data quality assessment metrics and intervention strategies in a sound and systematic way.

To the best of the authors' knowledge, this paper is the first data quality theory guided examination of DQA practices in RDRs.

The purpose of the study is to analyze a sample of 528 published papers over the past 11 years by conducting a bibliometric analysis. The study also aims to provide a consolidated overview of the existing literature on “gaming addiction” and presents the status of research with future directions for researchers who wish to explore and contribute to this rapidly evolving field. The descriptive statistics have been conducted through citation and co-citation analysis.

For the bibliometric analysis, the documents were retrieved from the Scopus database with the help of the Scopus analyzer while the VOS viewer1.6.16 software was used to analyze citations, co-authorship, etc. The literature search strategy was applied across various databases and the articles published between 2010 and December 2021 giving a total of 1,219 articles across all disciplines. Finally, 528 articles were shortlisted through the query restricted to subject areas, namely, business management, psychology, social science and multidisciplinary areas.

IGA has also been recognized by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, as one of the disorders; hence, this certainly calls for focussed efforts to understand the same and control further damage. The number of articles devoted to the study of “gaming addiction” has increased rapidly in recent years. Moreover, this study identifies some of the most influential articles in this area. Finally, this paper highlights the new trends and discusses the future research associated with gaming addiction.

This study focusses on gaming addiction and its trends, related to researchers and country-wise contributions. This is one of the few studies to review the literature on gaming addiction by using citation and co-citation analysis. The main findings of this paper will help academicians and practitioners to improve the body of knowledge on the topic and provide an overview of promising future research avenues.

Internet gaming is a newly emerging area and studies related to gaming addiction are very recent. To the best of the authors’ knowledge, this study is a unique and comprehensive overview of the leading works done in this area.

This paper focuses on the use of e-resources by research scholars and post-graduate students at Kashmir University. The main aim is to determine the use of e-resources, users skills in handling e-resources and the purpose of their use. Further, this paper aims to highlight the problems faced by research scholars and post-graduate students in accessing e-resources.

The survey was conducted through a structured questionnaire circulated among 250 research scholars, both (M.Phil./Ph.D.) and post-graduate students, from different departments of Kashmir University, and the response rate was 80%. Random sample method was used for the selection of respondents and interacting with them. The responses received from the research scholars to 14 questions are presented in the form of tables.

Major findings of the study reveal that the majority of the students reported using electronic journal resources for various purposes including working on assignments, research proposal writing, literature review writing, research report writing, current awareness and leisurely exploration of ongoing scientific debates through peer-reviewed papers. The challenges encountered in the use of electronic journal resources include a power outage, inadequate bandwidth, slow download speed, inability to access the resources from home, lack of training, lack of awareness, limited access to computers and difficulty in searching. The paper concludes that electronic resources have become an integral part of the information needs of research scholars’ post-graduate students at Kashmir University. Further, it finds that e-resources can be good substitutes for conventional resources, if the access is fast, and more computer terminals are installed to provide fast access to e-resources. Finally, recommendations for improving the use of electronic journal resources are provided.

The paper restrains the study exclusively to use of e-resources by the research scholars and post-graduate students of Kashmir University.

The paper highlights the use of e-resources by research scholars and post-graduate students of Kashmir University and makes some constructive suggestions for the improvement of electronic resources and services. This is the first time an effort has been made to assess the use of electronic resources by post-graduate students at Kashmir University. The study could be used to assess the post-graduate students’ needs for electronic resources at the Kashmir University and other users in higher learning institutions.

In order to estimate the value of semi-automated subject indexing in operative library catalogues, the study aimed to investigate five different automated implementations of an open source software package on a large set of Swedish union catalogue metadata records, with Dewey Decimal Classification (DDC) as the target classification system. It also aimed to contribute to the body of research on aboutness and related challenges in automated subject indexing and evaluation.

On a sample of over 230,000 records with close to 12,000 distinct DDC classes, an open source tool Annif, developed by the National Library of Finland, was applied in the following implementations: lexical algorithm, support vector classifier, fastText, Omikuji Bonsai and an ensemble approach combing the former four. A qualitative study involving two senior catalogue librarians and three students of library and information studies was also conducted to investigate the value and inter-rater agreement of automatically assigned classes, on a sample of 60 records.

The best results were achieved using the ensemble approach that achieved 66.82% accuracy on the three-digit DDC classification task. The qualitative study confirmed earlier studies reporting low inter-rater agreement but also pointed to the potential value of automatically assigned classes as additional access points in information retrieval.

The paper presents an extensive study of automated classification in an operative library catalogue, accompanied by a qualitative study of automated classes. It demonstrates the value of applying semi-automated indexing in operative information retrieval systems.