Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
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COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
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NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
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Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
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HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
The AMI meeting corpus: a pre-announcement
MLMI'05 Proceedings of the Second international conference on Machine Learning for Multimodal Interaction
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MLMI '08 Proceedings of the 5th international workshop on Machine Learning for Multimodal Interaction
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MLMI '08 Proceedings of the 5th international workshop on Machine Learning for Multimodal Interaction
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MLMI '08 Proceedings of the 5th international workshop on Machine Learning for Multimodal Interaction
Extrinsic Summarization Evaluation: A Decision Audit Task
MLMI '08 Proceedings of the 5th international workshop on Machine Learning for Multimodal Interaction
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ACM Transactions on Speech and Language Processing (TSLP)
Improving supervised learning for meeting summarization using sampling and regression
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Information Technology and Management
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IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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This paper explores the issue of term-weighting in the genre of spontaneous, multi-party spoken dialogues, with the intent of using such term-weights in the creation of extractive meeting summaries. The field of text information retrieval has yielded many term-weighting techniques to import for our purposes; this paper implements and compares several of these, namely tf.idf, Residual IDF and Gain. We propose that term-weighting for multi-party dialogues can exploit patterns in word usage among participant speakers, and introduce the su.idf metric as one attempt to do so. Results for all metrics are reported on both manual and automatic speech recognition (ASR) transcripts, and on both the ICSI and AMI meeting corpora.