ERIC Number: ED459822
Record Type: Non-Journal
Publication Date: 2001-Jun
Reference Count: N/A
Automatic Identification and Organization of Index Terms for Interactive Browsing.
Wacholder, Nina; Evans, David K.; Klavans, Judith L.
The potential of automatically generated indexes for information access has been recognized for several decades, but the quantity of text and the ambiguity of natural language processing have made progress at this task more difficult than was originally foreseen. Recently, a body of work on development of interactive systems to support phrase browsing has begun to emerge. This paper considers two issues related to the use of automatically identified phrases as index terms in a dynamic text browser (DTB), a user-centered system for navigating and browsing index terms: (1) What criteria are useful for assessing the usefulness of automatically identified index terms? (2) Is the quality of the terms identified by automatic indexing such that they provide useful access to document content? The terms this paper focuses on have been identified by LinkIT, a software tool for identifying significant topics in text. Over 90% of the terms identified by LinkIT are coherent and therefore merit inclusion in the dynamic text browser. Terms identified by LinkIT are input to Intell-Index, a prototype DTB that supports interactive navigation of index terms. The distinction between phrasal heads (the most important words in a coherent term) and modifiers serves as the basis for a hierarchical organization of terms. This linguistically motivated structure helps user to efficiently browse and disambiguate terms. The paper conclude that the approach to information access discussed is very promising, and that there is much room for further research. In the meantime, this research is a contribution to the establishment of a solid foundation for assessing the usability of terms in phrase browsing. (Contains 25 references.) (Author/AEF)
Descriptors: Access to Information, Data Processing, Indexes, Information Seeking, Information Systems, Natural Language Processing, Online Searching, Subject Index Terms
Association for Computing Machinery, 1515 Broadway, New York NY 10036. Tel: 800-342-6626 (Toll Free); Tel: 212-626-0500; e-mail: email@example.com. For full text: http://www1.acm.org/pubs/contents/proceedings/dl/379437/.
Publication Type: Numerical/Quantitative Data; Reports - Research; Speeches/Meeting Papers
Education Level: N/A
Sponsor: National Science Foundation, Arlington, VA.
Authoring Institution: N/A