A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
The Journal of Machine Learning Research
Identifying similarities, periodicities and bursts for online search queries
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Context-aware query suggestion by mining click-through and session data
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Query Expansion Using External Evidence
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Query dependent pseudo-relevance feedback based on wikipedia
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Multiple approaches to analysing query diversity
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Intent-Based Categorization of Search Results Using Questions from Web Q&A Corpus
WISE '09 Proceedings of the 10th International Conference on Web Information Systems Engineering
Visual query suggestion: Towards capturing user intent in internet image search
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
A structured approach to query recommendation with social annotation data
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
CONQUER: a system for efficient context-aware query suggestions
Proceedings of the 20th international conference companion on World wide web
Fine-grained class label markup of search queries
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Social annotation in query expansion: a machine learning approach
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
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Recently, query suggestions have become quite useful in web searches. Most provide additional and correct terms based on the initial query entered by users. However, query suggestions often recommend queries that differ from the user's search intentions due to different contexts. In such cases, faceted query expansions and their usages are quite efficient. In this paper, we propose faceted query expansion methods using the resources of Community Question Answering (CQA), which is social network service (SNS) that shares user knowledge. In a CQA site, users can post questions in a suitable category. Others answer them based on the category framework. Thus, the CQA "category" makes a "facet" of the query expansion. In addition, the time of year when the question was posted plays an important role in understanding its context. Thus, such seasonality creates another "facet" of the query expansion. We implement two-dimensional faceted query expansion methods based on the results of the Latent Dirichlet Allocation (LDA) analysis of CQA resources. The question articles deriving query expansion are provided for choosing appropriate terms by users. Our sophisticated evaluations using actual and long-term CQA resources, such as "Yahoo! CHIEBUKURO," demonstrate that most parts of the CQA questions are posted in periodicity and in bursts.