Disjunctive Sets of Phrase Queries for Diverse Query Suggestion
Ziyang Liao, Keishi Tajima · IEEE/WIC/ACM International Conference on Web Intelligence · 2019
This paper proposes a method of suggesting expanded queries that disambiguate the original Web query which has multiple interpretations. In order to produce a diverse set of queries including those corresponding to infrequent query intents, our method produces queries by extracting phrases connecting given query terms from a corpus. We use a corpus because infrequent query intents may not appear in query logs. We use phrase queries because we need sufficiently specific queries for retrieving pages corresponding to infrequent query intents out of many pages corresponding to popular query intents. Phrase queries usually have high accuracy but low recall. In order to also achieve high recall, we use a disjunction of many phrase queries as a query. Our method first produces many phrase queries by using term expansion and phrase extraction from a corpus, then group semantically similar phrases into clusters, and use each cluster as a disjunctive set of phrase queries.