ASIS&T 2006 - Multiple Access to PubMed: A proposal of utilizing MeSH as a term suggestion tool for PubMed bibliographic search

Multiple Access to PubMed: A proposal of utilizing MeSH as a term suggestion tool for PubMed bibliographic search

Muh-Chyun Tang*, Nikita Lytkin** *National Taiwan Universit; ** Rutgers University

ASIS&T Annual Meeting - 2006 (ASIS&T 2006)
Austin, Texas, November 3-9, 2006

Abstract

Origin of the Problem One of the critical problems faced by the user searching for a heterogeneous and massive bibliographic database such as PubMed is the difficulty of managing the returned results. Several system features of PubMed (e.g. default “explode” function and free-text indexing in title and abstract fields) that aim at facilitating end-user search tend to increase indexing exhaustivity and therefore favor search recall at the expense of precision. Faced with the unmanageable amount of returned results and without an efficient tool to systematically narrow down their searches, users are often left with few options but to hastily browse the first few returned pages. The consequence of information overload creates at least two barriers to a successful user-system communication. Firstly, there in no telling whether there might be documents relevant to users’ needs buried deep down in the returned set that never get the chance of being viewed. Secondly, the skimming of the surface of the returned set also gives incomplete feedback for the judgment of users’ query performance. We propose an interface that makes use the existing structure of MeSH (Medical Subject Headings) to help users manage search results.

The proposed solution: using MeSH as a term suggestion tool In an automatic indexing environment where the indexing exhaustivity is quite high, short queries usually produce unmanageably large returned sets. The lack of precision of the search can be alleviated, however, by eliciting longer queries from the user. To elicit more terms from users, we propose a term suggestion feature that utilizes the classification structure of MeSH. The tool involves extracting MeSH terms present in the returned set after the user submit her/his query. These terms are considered conceptually associated with the original query due to their co-occurrences in the retrieved records.

Extracted terms presentation It is crucial to organize and present the extracted MeSH terms in a manner that makes efficient browsing and selection possible. We plan to experiment and compare two ways of presenting the MeSH terms to the user. The baseline system will simply rank the terms based on their frequency in the original returned set. The other presentation method will organize the extracted terms using the 15 top-level semantic categories of MeSH. Terms co-occur with the initial query will be mapped against the MeSH tree with the non-occurring terms left out. Thus a filtered MeSH tree that includes only the extracted terms will be generated dynamically each time a query is submitted. The user will be given the option of browsing and selecting terms from the post-querying MeSH tree.

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