Experiments in automatic statistical thesaurus construction
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Query expansion using lexical-semantic relations
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Query expansion using local and global document analysis
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Improving the effectiveness of information retrieval with local context analysis
ACM Transactions on Information Systems (TOIS)
Information Retrieval: A Health and Biomedical Perspective
Information Retrieval: A Health and Biomedical Perspective
Verbs semantics and lexical selection
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Implementing clarification dialogues in open domain question answering
Natural Language Engineering
Joint categorization of queries and clips for web-based video search
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Evaluation campaigns and TRECVid
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Semantic similarity based on compact concept ontology
Proceedings of the 17th international conference on World Wide Web
Exploiting the query expansion through knowledgebases for images
IVIC'11 Proceedings of the Second international conference on Visual informatics: sustaining research and innovations - Volume Part II
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Query expansion has received extensive attention in information retrieval community. Although semantic based query expansion appears to be promising in improving retrieval performance, previous research has shown that it cannot consistently improve retrieval performance. It is a tricky problem to automatically determine whether to do query expansion for a given query. In this paper, we introduce Compact Concept Ontology (CCO) and provide users the option of exploring different semantic levels by using different CCOs. Experimental results show our approach is superior to previous work in many cases. Additionally, we integrate the proposed methods into a text-based video search system (iVSearcher ), to improve the user's experience and retrieval performance significantly. To the best of our knowledge, this is the first system that integrates semantic information into video search and explores different semantic levels.