Abstract
Aggregating search results from a variety of heterogeneous sources, i.e. so-called verticals [1], such as news, image, video and blog, into a single interface has become a popular paradigm in web search. In this paper, we present the results of a user study that collected more than 1,500 assessments of vertical intent over 320 web topics. Firstly, we show that users prefer diverse vertical content for many queries and that the level of inter-assessor agreement for the task is fair [2]. Secondly, we propose a methodology to predict the vertical intent of a query using a search engine log by exploiting click-through data, and show that it outperforms traditional approaches.
| Original language | English |
|---|---|
| Title of host publication | Advances in Information Retrieval |
| Subtitle of host publication | 34th European Conference on IR Research, ECIR 2012, Barcelona, Spain, April 1-5, 2012. Proceedings |
| Publisher | Springer |
| Pages | 499-502 |
| Number of pages | 4 |
| ISBN (Electronic) | 9783642289972 |
| ISBN (Print) | 9783642289965 |
| DOIs | |
| Publication status | Published - 2012 |
Publication series
| Name | Lecture Notes in Computer Science |
|---|---|
| Publisher | Springer Berlin Heidelberg |
| Volume | 7224 |
| ISSN (Print) | 0302-9743 |
Keywords
- web searching
- diverse vertical content
- inter-assessor agreement
- search engine log
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Cite this
Zhou, K., Cummins, R., Halvey, M., Lalmas, M., & Jose, J. M. (2012). Assessing and predicting vertical intent for web queries. In Advances in Information Retrieval: 34th European Conference on IR Research, ECIR 2012, Barcelona, Spain, April 1-5, 2012. Proceedings (pp. 499-502). (Lecture Notes in Computer Science; Vol. 7224). Springer. https://doi.org/10.1007/978-3-642-28997-2_50