The nature of indexing: how humans and machines analyze messages and texts for retrieval. Part I: Research, and the nature of human indexing

Anderson, James D.; Pérez-Carballo, José

doi:10.1016/s0306-4573(00)00026-1

Cited by 60 publications

(23 citation statements)

References 14 publications

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“…Mai (2001) uses a semiotic framework to underscore the inextricable link between the social and cultural background of the indexer and the interpretation of document content. In part one of an excellent state-of-the-art review of the nature of indexing, Anderson and Pêrez-Carballo (2001) survey the research on how humans process documents, interpret content, and assign index terms. It will be interesting to see whether, and how, studies of tagging by users will contribute to our understanding of content labeling.…”

Section: Thesaurimentioning

confidence: 99%

Thesauri and Facets and Tags, Oh My! A Look at Three Decades in Subject Analysis

Schwartz¹

2008

lib

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The field of subject analysis enjoyed a flurry of interest in the 1970s, and has recently become a focus of attention again. The scholarly community doing work in this area has become more diffuse, and has grown to include new groups, such as information architects. Changes in information services and information seeking have led to reexamination of the nature and role of subject analysis tools and practices. This selective review looks at thesauri, guided navigation, and folksonomy as three activity areas in which subject analysis researchers have been attempting to address rapidly changing new environments.

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Section: Thesaurimentioning

confidence: 99%

Thesauri and Facets and Tags, Oh My! A Look at Three Decades in Subject Analysis

Schwartz¹

2008

lib

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“…Some authors, Lancaster (2003) and Mai (1997) among them, analyze this procedure and the problems of identifying subjects. Others, such as Willis & Losee (2013) or Anderson (2001aAnderson ( , 2001b, review the most important aspects of manual and automatic subject indexing and also the differences between both systems.…”

Section: Literature Reviewmentioning

confidence: 99%

A semi-automatic indexing system based on embedded information in HTML documents

et al. 2015

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Purpose -This paper describes and evaluates the tool DigiDoc MetaEdit which allows the semi-automatic indexing of HTML documents. The tool works by identifying and suggesting keywords from a thesaurus according to the embedded information in HTML documents. This enables the parameterization of keyword assignment based on how frequently the terms appear in the document, the relevance of their position, and the combination of both.Design/methodology/approach -In order to evaluate the efficiency of the indexing tool, the descriptors/keywords suggested by the indexing tool are compared to the keywords which have been indexed manually by human experts. To make this comparison a corpus of HTML documents are randomly selected from a journal devoted to Library and Information Science.Findings -The results of the evaluation show that there: (1) is close to a 50% match or overlap between the two indexing systems, however if you take into consideration the related terms and the narrow terms the matches can reach 73%; and (2) the first terms identified by the tool are the most relevant.Originality/value -The tool presented identifies the most important keywords in an HTML document based on the embedded information in HTML documents. Nowadays, representing the contents of documents with keywords is an essential practice in areas such as information retrieval and e-commerce.

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“…Despite the fact that index languages do not make large differences in search performance, previous research has revealed that the usefulness of human-developed index terms is affected by several factors, such as the subject domain of document collection, nature of controlled vocabulary and skills of indexers and searchers (Svenonius, 1986). A controlled user experiment for assessing the specific impact of particular variables on search performance is complex because it is relatively difficult to isolate these factors (Anderson & Pérez-Carballo, 2001). A study that is designed to assess the impact of subject domain, characteristics of index languages, or searcher characteristics on user search performance is challenging in itself because of the difficulty of separating the factors and the possible interactions among them.…”

Section: Assessment Of Human-developed Index Termsmentioning

confidence: 99%

The impact of MeSH (Medical Subject Headings) terms on information seeking effectiveness

Liu

2009

SIGIR Forum

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To what extent do MeSH (Medical Subject Headings) terms improve search effectiveness of different kinds of users? We observed four different kinds of searchers using an experimental information retrieval (IR) system: (1) search novices; (2) domain experts; (3) search experts and (4) medical librarians. The information needs were a subset of the relatively difficult topics originally created for the Text REtrieval Conference (TREC). By experimental design, we used 20 search topics in an IR user experiment to alleviate search topic variability. Effectiveness of retrieval was based on the relevance judgments set provided by TREC. Thirty-two participants searched either using a version of the system in which abstracts and MeSH terms were displayed or another version in which they had to formulate their own terms based only on the display of abstracts. We found that MeSH terms were more useful for domain experts than for search experts in terms of the precision measure, even though domain experts did not perceive that MeSH terms were useful. We speculate that because of the technical topics, only the domain experts had the knowledge to understand and therefore make use of the MeSH terms. The primary contributions of this research are: (1) assessment of relative impact of searchers characteristics of domain knowledge and search training on search effectiveness and (2) design and methodology for assessing the usefulness of controlled vocabulary. The effort to create MeSH terms is worthwhile for domain experts' searches on technical topics.

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The nature of indexing: how humans and machines analyze messages and texts for retrieval. Part I: Research, and the nature of human indexing

Cited by 60 publications

References 14 publications

Thesauri and Facets and Tags, Oh My! A Look at Three Decades in Subject Analysis

Thesauri and Facets and Tags, Oh My! A Look at Three Decades in Subject Analysis

A semi-automatic indexing system based on embedded information in HTML documents

The impact of MeSH (Medical Subject Headings) terms on information seeking effectiveness

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