Temporal Query Intent Disambiguation using Time-Series Data

Conference paper (2016)

Authors

Yue Zhao Web Information Systems
Claudia Hauff Web Information Systems
Research Group
Web Information Systems
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Published Date

2016

Language

English

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Research Group

Web Information Systems

Abstract

Understanding temporal intents behind users' queries is essential to meet users' time-related information needs. In order to classify queries according to their temporal intent (e.g. Past or Future), we explore the usage of time-series data derived from Wikipedia page views as a feature source. While existing works leverage either proprietary search engine query logs or highly processed and aggregated data (such as Google Trends) for this purpose, we investigate the utility of a freely available data source for this purpose. Our experiments on the NTCIR-12 Temporalia-2 dataset show, that Wikipedia pageview-based time-series data can significantly improve the disambiguation of temporal intents for specific types of queries, in particular those without temporal expressions present in the query string.

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