Dynamic Query Completion Through Search Result Clustering

Abstract: Query completion is a feature employed by most modernsearch engines. These completions can be derived by different means. The most popular algorithm ranks completions by the frequency with which it appears in a database of old query logs. This project aims to investigate a new method for finding completions: namely through clustering search results and extracting terms from the clusters. To test the capabilities of this method, the project implemented the back-end to a search system, which includes the search result clustering algorithm Lingo. The system uses the output cluster labels as query completions. Two experiments were conducted, one for Informational queries and one for Navigational queries, each comparing the system to Apache Solr’s Suggester component. For Informational queries, a new way of scoring query completions was invented. The experiments showed that clustering performedbetter than the Suggester component for Informational queries, the results were inconclusive for Navigational queries.