Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Automatic combination of multiple ranked retrieval systems
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Combining multiple evidence from different properties of weighting schemes
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Retrieving spoken documents by combining multiple index sources
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic models of information retrieval based on measuring the divergence from randomness
ACM Transactions on Information Systems (TOIS)
Fusion Via a Linear Combination of Scores
Information Retrieval
Metasearch: data fusion for document retrieval
Metasearch: data fusion for document retrieval
Building an information retrieval test collection for spontaneous conversational speech
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Information fusion for spoken document retrieval
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04
Model Fusion Experiments for the CLSR Task at CLEF 2007
Advances in Multilingual and Multimodal Information Retrieval
Pitt at CLEF05: data fusion for spoken document retrieval
CLEF'05 Proceedings of the 6th international conference on Cross-Language Evalution Forum: accessing Multilingual Information Repositories
Terrier information retrieval platform
ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
Overview of the CLEF-2006 cross-language speech retrieval track
CLEF'06 Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrieval
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In this paper we present two novel model fusion techniques. We fuse together results from several Information Retrieval models or variations of the models. We test them on a collection of spontaneous speech transcripts. We also fuse results obtained with different documents representations (automatic transcripts or manual data). Our first fusion model is training the weighs based on the training data, but in an efficient and novel way. The second fusion model works for results with high variation, such as results obtained from automatic vs. manual document representations.