Agglomerative clustering of a search engine query log
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
ACM SIGIR Forum
Robust and flexible mixed-initiative dialogue for telephone services
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
Unsupervised word sense disambiguation rivaling supervised methods
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Understanding user goals in web search
Proceedings of the 13th international conference on World Wide Web
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
Optimizing web search using web click-through data
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Automatic identification of user goals in Web search
WWW '05 Proceedings of the 14th international conference on World Wide Web
Improving Automatic Query Classification via Semi-Supervised Learning
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Detecting online commercial intention (OCI)
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
Robust classification of rare queries using web knowledge
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Random walks on the click graph
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Automatic learning of dialogue strategy using dialogue simulation and reinforcement learning
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Predictive user click models based on click-through history
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Contextual advertising by combining relevance with click feedback
Proceedings of the 17th international conference on World Wide Web
Video suggestion and discovery for youtube: taking random walks through the view graph
Proceedings of the 17th international conference on World Wide Web
Simrank++: query rewriting through link analysis of the clickgraph (poster)
Proceedings of the 17th international conference on World Wide Web
To personalize or not to personalize: modeling queries with variation in user intent
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Learning query intent from regularized click graphs
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
SCOPE: easy and efficient parallel processing of massive data sets
Proceedings of the VLDB Endowment
Understanding the relationship between searchers' queries and information goals
Proceedings of the 17th ACM conference on Information and knowledge management
Proceedings of the 2009 workshop on Web Search Click Data
Second ACM International Conference on Web Search and Web Data Mining
Optimizing dialogue management with reinforcement learning: experiments with the NJFun system
Journal of Artificial Intelligence Research
Scalable multi-dimensional user intent identification using tree structured distributions
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
How many multiword expressions do people know?
MWE '11 Proceedings of the Workshop on Multiword Expressions: from Parsing and Generation to the Real World
Personalization of search profile using ant foraging approach
ICCSA'10 Proceedings of the 2010 international conference on Computational Science and Its Applications - Volume Part IV
Deriving query intents from web search engine queries
Journal of the American Society for Information Science and Technology
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Three methods are proposed to classify queries by intent (CQI), e.g., navigational, informational, commercial, etc. Following mixed-initiative dialog systems, search engines should distinguish navigational queries where the user is taking the initiative from other queries where there are more opportunities for system initiatives (e.g., suggestions, ads). The query intent problem has a number of useful applications for search engines, affecting how many (if any) advertisements to display, which results to return, and how to arrange the results page. Click logs are used as a substitute for annotation. Clicks on ads are evidence for commercial intent; other types of clicks are evidence for other intents. We start with a simple Naïve Bayes baseline that works well when there is plenty of training data. When training data is less plentiful, we back off to nearby URLs in a click graph, using a method similar to Word-Sense Disambiguation. Thus, we can infer that designer trench is commercial because it is close to www.saksfifthavenue.com, which is known to be commercial. The baseline method was designed for precision and the backoff method was designed for recall. Both methods are fast and do not require crawling webpages. We recommend a third method, a hybrid of the two, that does no harm when there is plenty of training data, and generalizes better when there isn't, as a strong baseline for the CQI task.