A simple relevancy‐ranking strategy for an interface to Boolean OPACs

Abstract

A relevancy‐ranking algorithm for a natural language interface to Boolean online public access catalogs (OPACs) was formulated and compared with that currently used in a knowledge‐based search interface called the E‐Referencer, being developed by the authors. The algorithm makes use of seven well‐known ranking criteria: breadth of match, section weighting, proximity of query words, variant word forms (stemming), document frequency, term frequency and document length. The algorithm converts a natural language query into a series of increasingly broader Boolean search statements. In a small experiment with ten subjects in which the algorithm was simulated by hand, the algorithm obtained good results with a mean overall precision of 0.42 and mean average precision of 0.62, representing a 27 percent improvement in precision and 41 percent improvement in average precision compared to the E‐Referencer. The usefulness of each step in the algorithm was analyzed and suggestions are made for improving the algorithm.