Abstract
We hypothesize that the variance in volume of high-velocity queries over time can be explained by observing that these queries are formulated in response to events in the world that users are interested in. Based on it, this paper describes a system, Zed, which automatically finds explanations for high velocity queries, by extracting descriptions of relevant and temporally-proximate events from the news stream. Zed can thus provide a meaningful explanation of what the general public is interested in at any time. We evaluated performance of several variant methods on top velocity “celebrity name” queries from Yahoo, using news stories from several sources for event extraction. Results bear out the event-causation hypothesis, in that Zed currently finds acceptable event-based explanations for about 90% of the queries examined.
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Jiang, M., Argamon, S., Chowdhury, A., Sidhu, K. (2006). ZED: Explaining Temporal Variations in Query Volume. In: Li, X., Zaïane, O.R., Li, Z. (eds) Advanced Data Mining and Applications. ADMA 2006. Lecture Notes in Computer Science(), vol 4093. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11811305_53
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DOI: https://doi.org/10.1007/11811305_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37025-3
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