Event-Driven Query Expansion

2020/12/22 by Guy Rosin, Guy D. Rosin, Ido Guy +4
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Information Retrieval and Search Behavior #Topic Modeling #Web Data Mining and Analysis #cs.CL #cs.IR

paper · pdf · doi:10.48550/arxiv.2012.12065

9 pages, WSDM 2021

arxiv created 2020/12/22 · openalex publication_date 2020/12/22 · arxiv updated 2020/12/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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.

Citations

• A Limited Memory Algorithm for Bound Constrained Optimization
• Distributed Representations of Words and Phrases and their Compositionality
• Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change
• Using Word Embeddings for Automatic Query Expansion
• Query Expansion Using Word Embeddings
• Word Translation Without Parallel Data
• Query Expansion with Locally-Trained Word Embeddings

Related

• Event-Centric Query Expansion in Web Search
• Query Expansion Using Word Embeddings
• Proactive Query Expansion for Streaming Data Using External Source
• Using Word Embeddings for Automatic Query Expansion
• Deep Neural Networks for Query Expansion using Word Embeddings