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SciFinder Scholar 2006: An Empirical Analysis of Research Topic Query Processing

A. Ben Wagner*

Science and Engineering Library, Arts and Sciences Libraries, University at Buffalo, 226 Capen Hall, Buffalo, New York 14260-1672

J. Chem. Inf. Model., 2006, 46 (2), pp 767–774

DOI: 10.1021/ci050481b

Publication Date (Web): February 24, 2006

Author phone: (716)645-2947 x230; e-mail: abwagner@buffalo.edu.

Abstract

Topical search queries in SciFinder Scholar are processed through an extensive set of natural language processing algorithms that greatly enhance the relevance and comprehensiveness of the search results. Little detailed documentation on these algorithms has been published. However, a careful examination of the highlighted hit terms coupled with a comparison of results from small variations in query language reveal much additional, useful information about these algorithms. An understanding of how these algorithms work can lead to better search results and explain many unexpected results, including differing hit counts for singular versus plural query words and phrases.

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Published In Issue March 27, 2006
Received November 1, 2005

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Article

SciFinder Scholar 2006: An Empirical Analysis of Research Topic Query Processing

Abstract

Tools

SciFinder Links

History

Recommend & Share

Related Content

The United Kingdom Chemical Database Service

SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rulesSMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules

Use of Structure−Activity Data To Compare Structure-Based Clustering Methods and Descriptors for Use in Compound Selection

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