Search (2413 results, page 2 of 121)

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Abstract

This paper presents a methodological discussion of a study of tagging quality in subject indexing. The data analysis in the study was divided into 3 phases: analysis of indexing consistency, analysis of tagging effectiveness, and analysis of the semantic values of tags. To analyze indexing consistency, this study employed the vector space model-based indexing consistency measures. An analysis of tagging effectiveness with tagging exhaustivity and tag specificity was conducted to ameliorate the drawbacks of consistency analysis based on only the quantitative measures of vocabulary matching. To further investigate the semantic values of tags at various levels of specificity, a latent semantic analysis (LSA) was conducted. To test statistical significance for the relation between tag specificity and semantic quality, correlation analysis was conducted. This research demonstrates the potential of tags for web document indexing with a complete assessment of tagging quality and provides a basis for further study of the strengths and limitations of tagging.

Theme

Social tagging

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Abstract

The purpose of this study is to understand users' motivations and intentions in the use of institutional collections on social tagging sites. Previous social tagging studies have collected social tagging data and analyzed how tagging functions as a tool to organize and retrieve information. Many studies focused on the patterns of tagging rather than the users' perspectives. To provide a more comprehensive picture of users' social tagging activities in institutional collections, and how this compares to social tagging in a more personal context, we collected data from social tagging users by surveying 7,563 participants in the Library of Congress's Flickr Collection. We asked users to describe their motivations for activities within the LC Flickr Collection in their own words using open-ended questions. As a result, we identified 11 motivations using a bottom-up, open-coding approach: affective reactions, opinion on photo, interest in subject, contribution to description, knowledge sharing, improving findability, social network, appreciation, personal use, and personal relationship. Our study revealed that affective or emotional reactions play a critical role in the use of social tagging of institutional collections by comparing our findings to existing frameworks for tagging motivations. We also examined the relationships between participants' occupations and our 11 motivations.

Theme

Social tagging

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Date

1. 8.2008 12:39:22

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Date

1. 8.2010 12:35:22

Theme

Social tagging

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Date

10. 9.2000 17:38:22

Theme

Social tagging

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Date

10. 9.2000 17:38:22

Theme

Social tagging

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Content

Inhalt: Keynote address - Order and KO - Conceptology in KO - Mathematics in KO - Psychology and KO - Science and KO - Problems in KO - KOS general questions - KOS structure and elements, facet analysis - KOS construction - KOS Maintenance, updating and storage - Compatibility, concordance, interoperability between indexing languages - Theory of classing and indexing - Taxonomies in communications engineering - Special KOSs in literature - Special KOSs in cultural sciences - General problems of natural language, derived indexing, tagging - Automatic language processing - Online retrieval systems and technologies - Problems of terminology - Subject-oriented terminology work - General problems of applied classing and indexing, catalogues, guidelines - Classing and indexing of non-book materials (images, archives, museums) - Personas and institutions in KO, cultural warrant - Organizing team - List of contributors

Date

22. 2.2013 12:09:34

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Abstract

Academic libraries have moved toward providing social networking features, such as tagging, in their library catalogs. To explore whether user tags can enhance access to individual literary works, the author obtained a sample of individual works of English and American literature from the twentieth and twenty-first centuries from a large academic library catalog and searched them in LibraryThing. The author compared match rates, the availability of subject headings and tags across various literary forms, and the terminology used in tags versus controlled-vocabulary headings on a subset of records. In addition, she evaluated the usefulness of available LibraryThing tags for the library catalog records that lacked subject headings. Options for utilizing the subject terms available in sources outside the local catalog also are discussed.

Date

10. 9.2000 17:38:22

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Abstract

Indexing consists of both novel and more traditional techniques. Cutting-edge indexing techniques, such as automatic indexing, ontologies, and topic maps, were developed independently of older techniques such as thesauri, but it is now recognized that these older methods also hold expertise. Indexing describes various traditional and novel indexing techniques, giving information professionals and students of library and information sciences a broad and comprehensible introduction to indexing. This title consists of twelve chapters: an Introduction to subject readings and theasauri; Automatic indexing versus manual indexing; Techniques applied in automatic indexing of text material; Automatic indexing of images; The black art of indexing moving images; Automatic indexing of music; Taxonomies and ontologies; Metadata formats and indexing; Tagging; Topic maps; Indexing the web; and The Semantic Web.

Date

24. 8.2016 14:03:22

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Date

22. 3.2023 12:00:14

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Abstract

Although user tagging of library resources shows substantial promise as a means of improving the quality of users' access to those resources, several important questions about the level and nature of the warrant for basing retrieval tools on user tagging are yet to receive full consideration by library practitioners and researchers. Among these is the simple evaluative question: What, specifically, are the factors that determine whether or not user-tagging services will be successful? If success is to be defined in terms of the effectiveness with which systems perform the particular functions expected of them (rather than simply in terms of popularity), an understanding is needed both of the multifunctional nature of tagging tools, and of the complex nature of users' mental models of that multifunctionality. In this paper, a conceptual framework is developed for the evaluation of systems that integrate user tagging with more traditional methods of library resource description.

Theme

Social tagging

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Content

In investigating the use of social tagging for knowledge organization and sharing, this paper reports on two case studies. Each study examines how two disparate communities of practices utilize social tagging to disseminate information to other community members in the online environment. Through the use of these tags, community members may retrieve and view relevant Web sites and online videos. The first study looks at tagging within the Code4Lib community of practice. The second study examines the use of tagging on video sharing sites used by a community of French teenagers. Uses of social tagging to share information within these communities are analyzed and discussed, and recommendations for future study are provided.

Theme

Social tagging

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Abstract

Data integration and mediation have become central concerns of information technology over the past few decades. With the advent of the Web and the rapid increases in the amount of data and the number of Web documents and users, researchers have focused on enhancing the interoperability of data through the development of metadata schemes. Other researchers have looked to the wealth of metadata generated by bookmarking sites on the Social Web. While several existing ontologies have capitalized on the semantics of metadata created by tagging activities, the Upper Tag Ontology (UTO) emphasizes the structure of tagging activities to facilitate modeling of tagging data and the integration of data from different bookmarking sites as well as the alignment of tagging ontologies. UTO is described and its utility in modeling, harvesting, integrating, searching, and analyzing data is demonstrated with metadata harvested from three major social tagging systems (Delicious, Flickr, and YouTube).

Theme

Social tagging

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Abstract

Social technologies tend to attract research on social structure or interaction. In this paper we analyze the individual use of a social technology, specifically an enterprise people-tagging application. We focus on active participants of the system and distinguish between users who initiate activity and those who respond to activity. This distinction is situated within the preferential attachment theory in order to examine which type of participant contributes more to the process of tagging. We analyze the usage of the people-tagging application in a snapshot representing 3 years of activity, focusing on self-tagging compared to tagging by and of others. The main findings are: (1) People who tag themselves are the most productive contributors to the system. (2) Preferential attachment saturation is reached at 12-14 tags per user. (3) The nature of participation is more significant than the number of participants for system growth. The paper concludes with theoretical and practical implications.

Theme

Social tagging

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Abstract

Large image collections on the Web need to be organized for effective retrieval. Metadata has a key role in image retrieval but rely on professionally assigned tags which is not a viable option. Current content-based image retrieval systems have not demonstrated sufficient utility on large-scale image sources on the web, and are usually used as a supplement to existing text-based image retrieval systems. We present two social tagging alternatives in the form of photo-sharing networks and image labeling games. Here we analyze these applications to evaluate their usefulness from the semantic point of view, investigating the management of social tagging for indexing. The findings of the study have shown that social tagging can generate a sizeable number of tags that can be classified as in terpretive for an image, and that tagging behaviour has a manageable and adjustable nature depending on tagging guidelines.

Theme

Social tagging

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Abstract

Social tagging systems enable users to assign arbitrary tags to various digital resources. However, they face vague-meaning problems when users retrieve or present resources with the keyword-based tags. In order to solve these problems, this study takes advantage of Semantic Web technology and the topological characteristics of knowledge maps to develop a system that comprises a semantic tagging mechanism and triple-pattern and visual searching mechanisms. A field experiment was conducted to evaluate the effectiveness and user acceptance of these mechanisms in a knowledge sharing context. The results show that the semantic social tagging system is more effective than a keyword-based system. The visualized knowledge map helps users capture an overview of the knowledge domain, reduce cognitive effort for the search, and obtain more enjoyment. Traditional keyword tagging with a keyword search still has the advantage of ease of use and the users had higher intention to use it. This study also proposes directions for future development of semantic social tagging systems.

Theme

Social tagging

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Content

This paper presents a longitudinal case study and analysis of tagging patterns in del.icio.us. Previous research has indicated that a tagging vocabulary will stabilize over time, suggesting that convergence may occur. This case study investigates the possibility of stability and convergence in a subset of the tagging vocabulary used with del.icio.us.

Theme

Social tagging

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Abstract

An increasingly difficult challenge in social tagging applications is negotiating the number of existing tags. This article examines the use of facets to facilitate the efficient organization and browsing of tags into manageable and distinct categories. Current and proposed methodologies for the application of facets in social tagging applications are evaluated. Results of this analysis indicate that these methodologies provide insufficient guidelines for the choice, evaluation, and maintenance of the facets. Suggestions are made to guide the design of a more rigorous methodology for the application of facets to social tagging applications.

Theme

Social tagging

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Abstract

The Specialized Information Services Division (SIS) of the National Library of Medicine (NLM) provides Web access to more than a dozen scientific databases on toxicology and the environment on TOXNET . Search queries on TOXNET often include misspelled or variant English words, medical and scientific jargon and chemical names. Following the example of search engines like Google and ClinicalTrials.gov, we set out to develop a spelling "suggestion" system for increased recall and precision in TOXNET searching. This paper describes development of dictionary technology that can be used in a variety of applications such as orthographic verification, writing aid, natural language processing, and information storage and retrieval. The design of the technology allows building complex applications using the components developed in the earlier phases of the work in a modular fashion without extensive rewriting of computer code. Since many of the potential applications envisioned for this work have on-line or web-based interfaces, the dictionaries and other computer components must have fast response, and must be adaptable to open-ended database vocabularies, including chemical nomenclature. The dictionary vocabulary for this work was derived from SIS and other databases and specialized resources, such as NLM's Unified Medical Language Systems (UMLS) . The resulting technology, A-Z Dictionary (AZdict), has three major constituents: 1) the vocabulary list, 2) the word attributes that define part of speech and morphological relationships between words in the list, and 3) a set of programs that implements the retrieval of words and their attributes, and determines similarity between words (ChemSpell). These three components can be used in various applications such as spelling verification, spelling aid, part-of-speech tagging, paraphrasing, and many other natural language processing functions.

Date

14. 8.2004 17:22:56

Source

Online. 28(2004) no.3, S.22-29