Event-Driven Query Expansion

TL;DR

This paper introduces a novel event-aware query expansion method that detects related events and embeds words and events in a shared vector space to improve web search retrieval performance.

Contribution

It presents a new approach to query expansion by jointly embedding words and events, enhancing the relevance of expanded queries for event-related searches.

Findings

Significant improvement over state-of-the-art methods in TREC datasets

Effective detection of event-related queries and related terms

Enhanced retrieval performance in newswire search tasks

Abstract

A significant number of event-related queries are issued in Web search. In this paper, we seek to improve retrieval performance by leveraging events and specifically target the classic task of query expansion. We propose a method to expand an event-related query by first detecting the events related to it. Then, we derive the candidates for expansion as terms semantically related to both the query and the events. To identify the candidates, we utilize a novel mechanism to simultaneously embed words and events in the same vector space. We show that our proposed method of leveraging events improves query expansion performance significantly compared with state-of-the-art methods on various newswire TREC datasets.