A fuzzy document retrieval system using the keyword connection matrix and a learning method
Fuzzy Sets and Systems - Special issue on applications of fuzzy systems theory, Iizuka '88
Evaluation of an inference network-based retrieval model
ACM Transactions on Information Systems (TOIS) - Special issue on research and development in information retrieval
Computer Evaluation of Indexing and Text Processing
Journal of the ACM (JACM)
Extended Boolean information retrieval
Communications of the ACM
A vector space model for automatic indexing
Communications of the ACM
Does organisation by similarity assist image browsing?
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
End-User Searching Challenges Indexing Practices inthe Digital Newspaper Photo Archive
Information Retrieval
Visually Searching the Web for Content
IEEE MultiMedia
WebSeer: An Image Search Engine for the World Wide Web
WebSeer: An Image Search Engine for the World Wide Web
Image Retrieval Using Multiple Evidence Ranking
IEEE Transactions on Knowledge and Data Engineering
Improving text categorization using the importance of sentences
Information Processing and Management: an International Journal
Automatic evaluation of summaries using N-gram co-occurrence statistics
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Towards optimal bag-of-features for object categorization and semantic video retrieval
Proceedings of the 6th ACM international conference on Image and video retrieval
The importance of query-concept-mapping for automatic video retrieval
Proceedings of the 15th international conference on Multimedia
Semantic text similarity using corpus-based word similarity and string similarity
ACM Transactions on Knowledge Discovery from Data (TKDD)
Web-based information content and its application to concept-based video retrieval
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Studying interaction methodologies in video retrieval
Proceedings of the VLDB Endowment
WordNet: similarity - measuring the relatedness of concepts
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Corpus-based and knowledge-based measures of text semantic similarity
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
LexRank: graph-based lexical centrality as salience in text summarization
Journal of Artificial Intelligence Research
Semantic context transfer across heterogeneous sources for domain adaptive video search
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Techniques for improving web retrieval effectiveness
Information Processing and Management: an International Journal
The effect of semantic relatedness measures on multi-label classification evaluation
Proceedings of the ACM International Conference on Image and Video Retrieval
Text similarity computing based on standard deviation
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
Can High-Level Concepts Fill the Semantic Gap in Video Retrieval? A Case Study With Broadcast News
IEEE Transactions on Multimedia
Adding Semantics to Detectors for Video Retrieval
IEEE Transactions on Multimedia
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Multimedia content has been growing quickly and video retrieval is regarded as one of the most famous issues in multimedia research. In order to retrieve a desirable video, users express their needs in terms of queries. Queries can be on object, motion, texture, color, audio, etc. Low-level representations of video are different from the higher level concepts which a user associates with video. Therefore, query based on semantics is more realistic and tangible for end user. Comprehending the semantics of query has opened a new insight in video retrieval and bridging the semantic gap. However, the problem is that the video needs to be manually annotated in order to support queries expressed in terms of semantic concepts. Annotating semantic concepts which appear in video shots is a challenging and time-consuming task. Moreover, it is not possible to provide annotation for every concept in the real world. In this study, an integrated semantic-based approach for similarity computation is proposed with respect to enhance the retrieval effectiveness in concept-based video retrieval. The proposed method is based on the integration of knowledge-based and corpus-based semantic word similarity measures in order to retrieve video shots for concepts whose annotations are not available for the system. The TRECVID 2005 dataset is used for evaluation purpose, and the results of applying proposed method are then compared against the individual knowledge-based and corpus-based semantic word similarity measures which were utilized in previous studies in the same domain. The superiority of integrated similarity method is shown and evaluated in terms of Mean Average Precision (MAP).