Abstract not found

This research presents an algorithmic approach to addressing the vocabulary problem in scientific information retrieval and information sharing, using the molecular biology domain as an example. We first present a literature review of cognitive stud!es related to the vcrcabulaw problem and vocabulary-based search aids (thesauri) and then discuss technques for building robust and domain-specific thesauri to assist in cross-domain scientific information retrieval. Using a variation of the automatic thesaurus generation techniques, which we refer to as the concept space approach, we racentiy conducted an experiment in the molecular biology domain in whch we created a C. eksgans worm thesaurus of 7,657 worm-specific terms and a Drosophila fty thesaurus of 15,626 terms. About 30 % of these terms overtappad, which created vocabulary paths

ueries using all search facets identified from requests, low complexity was achieved by formulating queries with major facets only. Query expansion was based on a thesaurus, from which the expansion keys were elicited for queries. There were five expansion types: (1) the first query version was an unexpanded, original query with one search key for each search concept (original search concepts) elicited from the test thesaurus; (2) the synonyms of the original search keys were added to the original query; (3) search keys representing the narrower concepts of the original search concepts were added to the original query; (4) search keys representing the associative concepts of the original search concepts were added to the original query; (5) all previous expansion keys were cumulatively added to the original query. Query structure refers to the syntactic structure of a query expression, marked with query operators and parentheses. The structure of queries was either weak (queries with n

this article, we report research on an algorithmic ap- gather, process, and retrieve information. These systems proach to alleviating search uncertainty in a large infor- provide a wide variety of information and services, rang- mation space. Grounded on object filtering, automatic ing from daily updates of foreign and national news, indexing, and co-occurrence analysis, we performed a movie reviews and clips, law cases, and financial data large-scale experiment using a parallel supercomputer on companies to journal articles, books, trademarks, and ( SGI Power Challenge ) to analyze 400,000/ abstracts in an INSPEC computer engineering collection. Two sys- statistics. However, gaining access to such information is tem-generated thesauri, one based on a combined ob- often difficult. This is due, in large part, to the indetermin- ject filtering and automatic indexing method, and the ism involved in the process by which information is in- other based on automatic indexing only, were compared dexed, and to the latitude searchers have in expressing a with the human-generated INSPEC subject thesaurus. query. Our user evaluation revealed that the system-generated thesauri were better than the INSPEC thesaurus in concept recall, but in concept precision the 3 thesauri were 2. Using Thesauri to Alleviate Search comparable. Our analysis also revealed that the terms suggested by the 3 thesauri were complementary and Uncertainty: Literature Review could be used to significantly increase "variety" in search terms and thereby reduce search uncertainty

Abstract-An intermediary expert system (IES) helps both end users and professional searchers to conduct their online database searching. To provide advice about term selec-tion and query expansion, an IES should include a terminological knowledge structure. Terminological attributes as well as other properties could provide the starting point for building a knowledge base, and knowledge acquisition could rely on knowledge-base techniques coupled with statistical techniques. The searching behavior of expert online searchers would provide one source of knowledge. The knowledge structure would include three constructs for each term: frequency data, a hedge, and a position in a classification scheme. Switching vocabularies or languages could provide a meta-schema and facilitate the interoperability of databases in similar subject domains. To develop such knowledge structure, future research should focus on terminological attributes, word and phrase disambiguation, automated text processing, and the role of thesauri and clas-sification schemes in indexing and retrieval. In particular, such research should develop techniques that combine knowledge-base and statistical methods and that consider user preferences. 1.

Abstract not found