Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Agglomerative clustering of a search engine query log
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Clustering user queries of a search engine
Proceedings of the 10th international conference on World Wide Web
Identifying similarities, periodicities and bursts for online search queries
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Hourly analysis of a very large topically categorized web query log
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Semantic similarity between search engine queries using temporal correlation
WWW '05 Proceedings of the 14th international conference on World Wide Web
Practical privacy: the SuLQ framework
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Context-sensitive information retrieval using implicit feedback
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Generating query substitutions
Proceedings of the 15th international conference on World Wide Web
Mining long-term search history to improve search accuracy
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
A large-scale analysis of query logs for assessing personalization opportunities
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Why we search: visualizing and predicting user behavior
Proceedings of the 16th international conference on World Wide Web
A large-scale evaluation and analysis of personalized search strategies
Proceedings of the 16th international conference on World Wide Web
Measuring semantic similarity between words using web search engines
Proceedings of the 16th international conference on World Wide Web
Information re-retrieval: repeat queries in Yahoo's logs
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Extracting semantic relations from query logs
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Query suggestions using query-flow graphs
Proceedings of the 2009 workshop on Web Search Click Data
Estimating Ad Clickthrough Rate through Query Intent Analysis
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Search the web x.0: mining and recommending web-mediated processes
Proceedings of the third ACM conference on Recommender systems
Characterizing commercial intent
Proceedings of the 18th ACM conference on Information and knowledge management
Large scale query log analysis of re-finding
Proceedings of the third ACM international conference on Web search and data mining
Optimal distance bounds for fast search on compressed time-series query logs
ACM Transactions on the Web (TWEB)
Do you want to take notes?: identifying research missions in Yahoo! search pad
Proceedings of the 19th international conference on World wide web
Query similarity by projecting the query-flow graph
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Taking advantage of contextualized interactions while users watch TV
Multimedia Tools and Applications
UIST '10 Adjunct proceedings of the 23nd annual ACM symposium on User interface software and technology
Paraphrasing with search engine query logs
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
ACM Transactions on Management Information Systems (TMIS)
Understanding and predicting personal navigation
Proceedings of the fourth ACM international conference on Web search and data mining
Shopping for products you don't know you need
Proceedings of the fourth ACM international conference on Web search and data mining
Improving recommendation for long-tail queries via templates
Proceedings of the 20th international conference on World wide web
Characterizing the usability of interactive applications through query log analysis
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Query reformulation mining: models, patterns, and applications
Information Retrieval
Enabling direct interest-aware audience selection
Proceedings of the 21st ACM international conference on Information and knowledge management
From cookies to cooks: insights on dietary patterns via analysis of web usage logs
Proceedings of the 22nd international conference on World Wide Web
Discovering tasks from search engine query logs
ACM Transactions on Information Systems (TOIS)
From devices to people: attribution of search activity in multi-user settings
Proceedings of the 23rd international conference on World wide web
Investigating query bursts in a web search engine
Web Intelligence and Agent Systems
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In this article, we demonstrate the value of long-term query logs. Most work on query logs to date considers only short-term (within-session) query information. In contrast, we show that long-term query logs can be used to learn about the world we live in. There are many applications of this that lead not only to improving the search engine for its users, but also potentially to advances in other disciplines such as medicine, sociology, economics, and more. In this article, we will show how long-term query logs can be used for these purposes, and that their potential is severely reduced if the logs are limited to short time horizons. We show that query effects are long-lasting, provide valuable information, and might be used to automatically make medical discoveries, build concept hierarchies, and generally learn about the sociological behavior of users. We believe these applications are only the beginning of what can be done with the information contained in long-term query logs, and see this work as a step toward unlocking their potential.