WordNet: a lexical database for English
Communications of the ACM
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
Using Association Rules to Discover Search Engines Related Queries
LA-WEB '03 Proceedings of the First Conference on Latin American Web Congress
Discovery of inference rules for question-answering
Natural Language Engineering
Generating query substitutions
Proceedings of the 15th international conference on World Wide Web
Mining search engine query logs for query recommendation
Proceedings of the 15th international conference on World Wide Web
A hierarchical phrase-based model for statistical machine translation
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Yago: a core of semantic knowledge
Proceedings of the 16th international conference on World Wide Web
Studying the use of popular destinations to enhance web search interaction
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
Using the wisdom of the crowds for keyword generation
Proceedings of the 17th international conference on World Wide Web
Leveraging popular destinations to enhance Web search interaction
ACM Transactions on the Web (TWEB)
Learning about the world through long-term query logs
ACM Transactions on the Web (TWEB)
Simrank++: query rewriting through link analysis of the click graph
Proceedings of the VLDB Endowment
Query suggestion using hitting time
Proceedings of the 17th ACM conference on Information and knowledge management
The query-flow graph: model and applications
Proceedings of the 17th ACM conference on Information and knowledge management
Matching task profiles and user needs in personalized web search
Proceedings of the 17th ACM conference on Information and knowledge management
Named entity recognition in query
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Extracting structured information from user queries with semi-supervised conditional random fields
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Learning entailment rules for unary templates
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Anatomy of the long tail: ordinary people with extraordinary tastes
Proceedings of the third ACM international conference on Web search and data mining
Towards rich query interpretation: walking back and forth for mining query templates
Proceedings of the 19th international conference on World wide web
Clustering query refinements by user intent
Proceedings of the 19th international conference on World wide web
Synthesizing high utility suggestions for rare web search queries
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Unsupervised transactional query classification based on webpage form understanding
Proceedings of the 20th ACM international conference on Information and knowledge management
Assisting web search users by destination reachability
Proceedings of the 20th ACM international conference on Information and knowledge management
Proceedings of the 20th ACM international conference on Information and knowledge management
Sequence clustering and labeling for unsupervised query intent discovery
Proceedings of the fifth ACM international conference on Web search and data mining
Unsupervised extraction of template structure in web search queries
Proceedings of the 21st international conference on World Wide Web
Modeling transactional queries via templates
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
Learning to suggest: a machine learning framework for ranking query suggestions
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Efficient query recommendations in the long tail via center-piece subgraphs
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Automatic suggestion of query-rewrite rules for enterprise search
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Collaborative ranking: improving the relevance for tail queries
Proceedings of the 21st ACM international conference on Information and knowledge management
Query recommendation for children
Proceedings of the 21st ACM international conference on Information and knowledge management
Gumshoe quality toolkit: administering programmable search
Proceedings of the 21st ACM international conference on Information and knowledge management
Proceedings of the sixth ACM international conference on Web search and data mining
Unsupervised identification of synonymous query intent templates for attribute intents
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Mining search and browse logs for web search: A Survey
ACM Transactions on Intelligent Systems and Technology (TIST) - Survey papers, special sections on the semantic adaptive social web, intelligent systems for health informatics, regular papers
Learning to rank query suggestions for adhoc and diversity search
Information Retrieval
Analyzing, Detecting, and Exploiting Sentiment in Web Queries
ACM Transactions on the Web (TWEB)
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The ability to aggregate huge volumes of queries over a large population of users allows search engines to build precise models for a variety of query-assistance features such as query recommendation, correction, etc. Yet, no matter how much data is aggregated, the long-tail distribution implies that a large fraction of queries are rare. As a result, most query assistance services perform poorly or are not even triggered on long-tail queries. We propose a method to extend the reach of query assistance techniques (and in particular query recommendation) to long-tail queries by reasoning about rules between query templates rather than individual query transitions, as currently done in query-flow graph models. As a simple example, if we recognize that 'Montezuma' is a city in the rare query "Montezuma surf" and if the rule 'city surf → beach has been observed, we are able to offer "Montezuma beach" as a recommendation, even if the two queries were never observed in a same session. We conducted experiments to validate our hypothesis, first via traditional small-scale editorial assessments but more interestingly via a novel automated large scale evaluation methodology. Our experiments show that general coverage can be relatively increased by 24% using templates without penalizing quality. Furthermore, for 36% of the 95M queries in our query flow graph, which have no out edges and thus could not be served recommendations, we can now offer at least one recommendation in 98% of the cases.