Probabilistic query expansion using query logs
Proceedings of the 11th international conference on World Wide Web
Large scale multi-label classification via metalabeler
Proceedings of the 18th international conference on World wide web
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
Classifying what-type questions by head noun tagging
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Semantic tagging of web search queries
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
Clustering query refinements by user intent
Proceedings of the 19th international conference on World wide web
Structured annotations of web queries
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
CrowdSearch: exploiting crowds for accurate real-time image search on mobile phones
Proceedings of the 8th international conference on Mobile systems, applications, and services
Understanding the semantic structure of noun phrase queries
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Facet discovery for structured web search: a query-log mining approach
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Crowdsourcing translation: professional quality from non-professionals
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Learning search tasks in queries and web pages via graph regularization
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Crowdsourcing for information retrieval
ACM SIGIR Forum
Sequence clustering and labeling for unsupervised query intent discovery
Proceedings of the fifth ACM international conference on Web search and data mining
Query recommendation using query logs in search engines
EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
Unsupervised extraction of template structure in web search queries
Proceedings of the 21st international conference on World Wide Web
CrowdER: crowdsourcing entity resolution
Proceedings of the VLDB Endowment
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Structured Web search incorporating data from structured sources into search engine results has attracted much attention from both academic and industrial communities. To understand user's intent, query structure interpretation is proposed to analyze the structure of queries in a query log and map query terms to the semantically relevant attributes of data sources in a target domain. Existing methods assume all queries should be classified to the target domain, and thus they are limited when interpreting queries from different domains in real query logs. To address the problem, we introduce a human-machine hybrid method by utilizing crowdsourcing platforms. Our method selects a small number of query terms and asks the crowdsourcing workers to interpret them, and then infers the interpretations based on the crowdsourcing results. To improve the performance, we propose an iterative probabilistic inference method based on a similarity graph of query terms, and select the most useful query terms for crowdsourcing by considering their domain-relevance and gained benefit. We evaluate our method on a real query log, and the experimental results show that our method outperforms the state-of-the-art method.