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.
| Original language | English |
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| Title of host publication | Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, SIGIR 2016 |
| Place of Publication | New York, NY |
| Publisher | Association for Computing Machinery (ACM) |
| Pages | 1017-1020 |
| Number of pages | 4 |
| ISBN (Print) | 978-1-4503-4069-4 |
| Publication status | Published - 2016 |
| Event | 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2016 - Pisa, Italy Duration: 17 Jul 2016 → 21 Jul 2016 |
Conference
| Conference | 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2016 |
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| Country/Territory | Italy |
| City | Pisa |
| Period | 17/07/16 → 21/07/16 |
Keywords
- Information systems
- Information retrieval
- Information retrieval query processing
- Query intent