Towards a user-oriented thesaurus for non-domain-specific image collections

被引:18
作者
Yoon, JungWon [1 ]
机构
[1] Univ S Florida, Sch Lib & Informat Sci, Tampa, FL 33620 USA
关键词
Image indexing; Social tagging; Thesaurus; ACCESS; EXPLORATION; RETRIEVAL; KNOWLEDGE;
D O I
10.1016/j.ipm.2009.03.004
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This study explored how user-supplied tags can be applied to designing a thesaurus that reflects the unique features of image documents. Tags from the popular image-sharing Web site Flickr were examined in terms of two central components of a thesaurus-selected concepts and their semantic relations-as well as the features of image documents. Shatford's facet category and Rosch et al.'s basic-level theory were adopted for examining concepts to be included in a thesaurus. The results suggested that the best approach to Color and Generic category descriptors is to focus on basic-level terms and to include frequently used superordinate- and subordinate-level terms. In the Abstract category, it was difficult to specify a set of abstract terms that can be used consistently and dominantly, so it was suggested to enhance browsability using hierarchical and associative relations. Study results also indicate a need for greater inclusion of Specific category terms, which were shown to be an important tool in establishing related tags. Regarding semantic relations, the study indicated that in the identification of related terms, it is important that descriptors not be limited only to the category in which a main entry belongs but broadened to include terms from other categories as well. Although future studies are needed to ensure the effectiveness of this user-oriented approach, this study yielded promising results, demonstrating that user-supplied tags can be a helpful tool in selecting concepts to be included in a thesaurus and in identifying semantic relations among the selected concepts. It is hoped that the results of this study will provide a practical guideline for designing a thesaurus for image documents that takes into account both the unique features of these documents and the unique information-seeking behaviors of general users. Published by Elsevier Ltd.
引用
收藏
页码:452 / 468
页数:17
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