SciFinder Scholar 2006: an empirical analysis of research topic query processing.
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.
Wagner
A Ben
AB
Science and Engineering Library, Arts and Sciences Libraries, University at Buffalo, 226 Capen Hall, Buffalo, New York 14260-1672, USA. abwagner@buffalo.edu
D000465:Algorithms; D019992:Databases as Topic; D007255:Information Services / Q000706:statistics & numerical data / Q000639:trends*; D015394:Molecular Structure; D009323:Natural Language Processing; D012107:Research Design; D012984:Software; D014584:User-Computer Interface