@inproceedings{dan2012mining,
author = {Dan, Ovidiu and Dmitriev, Pavel and White, Ryen W.},
title = {Mining for Insights in the Search Engine Query Stream},
booktitle = {21st International World Wide Web Conference (WWW 2012), Pages: 489-490 Lyon, France},
year = {2012},
month = {April},
abstract = {Search engines record a large amount of metadata each time a user issues a query. While efficiently mining this data can be challenging, the results can be useful in multiple ways, including monitoring search engine performance, improving search relevance, prioritizing research, and optimizing day-to-day operations. In this poster, we describe an approach for mining query log data for actionable insights – specific query segments (sets of queries) that require attention, and actions that need to be taken to improve the segments. Starting with a set of important metrics, we identify query segments that are “interesting” with respect to these metrics using a distributed frequent itemset mining algorithm.},
url = {http://approjects.co.za/?big=en-us/research/publication/mining-insights-search-engine-query-stream/},
pages = {489-490},
edition = {21st International World Wide Web Conference (WWW 2012), Pages: 489-490 Lyon, France},
}