Properties of optimally weighted data fusion in CBMIR
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Linking online news and social media
Proceedings of the fourth ACM international conference on Web search and data mining
Fusing heterogeneous modalities for video and image re-ranking
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Machine learning models: combining evidence of similarity for XML schema matching
KDXD'06 Proceedings of the First international conference on Knowledge Discovery from XML Documents
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Abstract: Fusion of various retrieval strategies has long been suggested as a means of improving retrieval effectiveness. To date, testing of fusion was done by combining result sets from widely disparate approaches that include an uncontrolled mixture of retrieval strategies and utilities. To isolate the effect of fusion on individual retrieval models, we have implemented probabilistic, vector space, and weighted Boolean models and tested the effect of fusion on these strategies in a systematic fashion. We also tested the effect of fusion on various query representations and have shown up to a twelve percent improvement in average precision.