Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
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Determining the user intent of web search engine queries
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Conditional random fields for activity recognition
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User intention based personalized search: HPS(hierarchical phrase search)
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SPIRE'06 Proceedings of the 13th international conference on String Processing and Information Retrieval
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Ubiquitous search of the physical world has recently received significant attention. In this paper, we investigate situation analysis based user intention recognition, which can be useful to retrieve information that may perfectly satisfy a user's needs. We first introduce a hierarchical user intention model based on CRFs (Conditional Random Fields). With the model, a BP (Belief Propagation) based inference method is proposed to recognize user search intention based on situation analysis. A variety of sensing mechanisms are adopted to collect context information of the physical world for robust and reliable situation analysis. We developed a prototype in a real home setting and experiments were performed to examine the effectiveness of the proposed approach.