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Knowledge organization systems and their consequences for information retrieval

Traditionally, research on knowledge organization systems (KOS) and information retrieval discussed the relative advantages or disadvantages of using controlled vocabularies versus free-text or intellectual indexing versus automatic indexing methods for indexing and search. Experiments and case studies variously showed the superiority of either approach without reaching a final conclusion on this seemingly basic question. As full-text indexing has become more possible and now prevalent, the discussion of the relative merits of KOS – not only as substitute but in combination with full-text – was not settled but continued with new challenges. With the advent of the Semantic Web, KOS (now appearing as ontologies) became important tools in new information retrieval applications and were pushed once again to the research forefront. With different disciplines working in the field, the terminology around KOS has become more and more ambiguous up to the point that tracing research in the literature is difficult – ironically something that traditional KOS have always tried to mitigate. This paper summarizes recent discussions of the impact of KOS on information retrieval and attempts to show and unify different research strands from library science research on subject indexing, information retrieval and the Semantic Web. Whereas earlier impact studies on retrieval resulted in clearly measurable outcomes (for example changes in precision / recall), recent use of KOS in Semantic Web applications or other information systems has switched from pure search scenarios to exploration (browse) and contextualization, for which clear (and calculable) evaluation or quality standards and benchmarks do not exist.

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Talk
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English
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Tagging behaviour with support from controlled vocabulary

The paper investigates how knowledge structures from a controlled vocabulary affect tagging. The study is a comparative analysis of tags assigned in two tagging systems - a simple tagging system (control system) that provides suggestions from two tag clouds (all users tags and my tags), and an enhanced tagging system (experimental system) that additionally offers suggestions from the Dewey Decimal Classification system (DDC). In the experimental study, 28 political students completed four tagging tasks, each comprising 15 documents. The focus was to examine how suggestions from the enhanced tagging system affect tags as regard tag specificity, exhaustivity, and novelty. Generally, there were no big differences between assigned tags from the two systems. The largest difference was a higher degree of tag specificity in the enhanced system indicating that suggestions from a controlled vocabulary might help taggers in being more specific in their tagging, allowing more precise information searching based on user tags. In addition, the results indicate that structured controlled suggestions might encourage taggers to add synonym variations enhancing the variety and number of access points. Furthermore, controlled vocabularies might be useful for automatic spell checking. Future study should explore in what direction the different kinds of suggestions lead the tagger and whether it is possible to identify scope or patterns between related tags from the two systems.

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Talk
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English
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An evaluation of enhancing social tagging with a knowledge organization system

Traditional subject indexing and classification are considered infeasible in many digital collections. Automated means and social tagging are often suggested as the two possible solutions. Both, however, have disadvantages and, depending on the purpose of use or context, require additional manual input. This study investigates ways of enhancing social tagging via knowledge organization systems, with a view to improving the quality of tags for increased information discovery and retrieval performance. Benefits of using both social tags and controlled terms are also explored, including enriching knowledge organization systems with new concepts.

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Talk
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English
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