Agglomerative clustering of a search engine query log
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Learning search engine specific query transformations for question answering
Proceedings of the 10th international conference on World Wide Web
Model-based feedback in the language modeling approach to information retrieval
Proceedings of the tenth international conference on Information and knowledge management
Query clustering using user logs
ACM Transactions on Information Systems (TOIS)
Probabilistic query expansion using query logs
Proceedings of the 11th international conference on World Wide Web
Optimizing web search using web click-through data
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Accurately interpreting clickthrough data as implicit feedback
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Query chains: learning to rank from implicit feedback
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Generating query substitutions
Proceedings of the 15th international conference on World Wide Web
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
Random walk with restart: fast solutions and applications
Knowledge and Information Systems
Optimizing relevance and revenue in ad search: a query substitution approach
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Query suggestion using hitting time
Proceedings of the 17th ACM conference on Information and knowledge management
Online expansion of rare queries for sponsored search
Proceedings of the 18th international conference on World wide web
Refined experts: improving classification in large taxonomies
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Entropy-biased models for query representation on the click graph
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Query recommendation using query logs in search engines
EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
Learning similarity function for rare queries
Proceedings of the fourth ACM international conference on Web search and data mining
Recommendations for the long tail by term-query graph
Proceedings of the 20th international conference companion on World wide web
Query suggestions in the absence of query logs
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Post-ranking query suggestion by diversifying search results
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Empirical Study on Rare Query Characteristics
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Query suggestion by constructing term-transition graphs
Proceedings of the fifth ACM international conference on Web search and data mining
Generating suggestions for queries in the long tail with an inverted index
Information Processing and Management: an International Journal
Structured query suggestion for specialization and parallel movement: effect on search behaviors
Proceedings of the 21st international conference on World Wide Web
Adaptive query suggestion for difficult queries
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
New assessment criteria for query suggestion
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Role-explicit query identification and intent role annotation
Proceedings of the 21st ACM international conference on Information and knowledge management
Collaborative ranking: improving the relevance for tail queries
Proceedings of the 21st ACM international conference on Information and knowledge management
Efficient fuzzy search in large text collections
ACM Transactions on Information Systems (TOIS)
Query suggestions for textual problem solution repositories
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Ontology-based personalised retrieval in support of reminiscence
Knowledge-Based Systems
Utilizing query change for session search
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Task-aware query recommendation
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Learning to personalize query auto-completion
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Query change as relevance feedback in session search
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Evaluating and predicting user engagement change with degraded search relevance
Proceedings of the 22nd international conference on World Wide Web
When do people use query suggestion? A query suggestion log analysis
Information Retrieval
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Query suggestion has been an effective approach to help users narrow down to the information they need. However, most of existing studies focused on only popular/head queries. Since rare queries possess much less information (e.g., clicks) than popular queries in the query logs, it is much more difficult to efficiently suggest relevant queries to a rare query. In this paper, we propose an optimal rare query suggestion framework by leveraging implicit feedbacks from users in the query logs. Our model resembles the principle of pseudo-relevance feedback which assumes that top-returned results by search engines are relevant. However, we argue that the clicked URLs and skipped URLs contain different levels of information and thus should be treated differently. Hence, our framework optimally combines both the click and skip information from users and uses a random walk model to optimize the query correlation. Our model specifically optimizes two parameters: (1) the restarting (jumping) rate of random walk, and (2) the combination ratio of click and skip information. Unlike the Rocchio algorithm, our learning process does not involve the content of the URLs but simply leverages the click and skip counts in the query-URL bipartite graphs. Consequently, our model is capable of scaling up to the need of commercial search engines. Experimental results on one-month query logs from a large commercial search engine with over 40 million rare queries demonstrate the superiority of our framework, with statistical significance, over the traditional random walk models and pseudo-relevance feedback models.