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Using citations to generate surveys of scientific paradigms

Using citations to generate surveys of scientific paradigms

引用

human language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, NAACL HLT 2009

作者： Mohammad, Saif Dorr, Bonnie Egan, Melissa Hassan, Ahmed Muthukrishan, Pradeep Qazvinian, Vahed Radev, Dragomir Zajic, David Institute for Advanced Computer Studies University of Maryland United States Computer Science University of Maryland United States Human Language Technology Center of Excellence United States Center for Advanced Study of Language United States Department of Electrical Engineering and Computer Science University of Michigan United States School of Information University of Michigan United States

ISBN: (纸本)9781932432411

The number of research publications in various disciplines is growing exponentially. Researchers and scientists are increasingly finding themselves in the position of having to quickly understand large amounts of technical material. In this paper we present the first steps in producing an automatically generated, readily consumable, technical survey. Specifically we explore the combination of citation information and summarization techniques. Even though prior work (Teufel et al., 2006) argues that citation text is unsuitable for summarization, we show that in the framework of multi-document survey creation, citation texts can play a crucial role. © 2009 Association for Computational Linguistics.

关键词： Surveys

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Generating high-coverage semantic orientation lexicons from overtly marked words and a thesaurus

Generating high-coverage semantic orientation lexicons from ...

引用

2009 Conference on Empirical Methods in Natural language processing, EMNLP 2009, Held in Conjunction with ACL-IJCNLP 2009

作者： Mohammad, Saif Dunne, Cody Dorr, Bonnie Laboratory for Computational Linguistics and Information Processing University of Maryland United States Human-Computer Interaction Lab. University of Maryland United States Institute for Advanced Computer Studies University of Maryland United States Department of Computer Science University of Maryland United States Human Language Technology Center of Excellence United States

Sentiment analysis often relies on a semantic orientation lexicon of positive and negative words. A number of approaches have been proposed for creating such lexicons, but they tend to be computationally expensive, and usually rely on significant manual annotation and large corpora. Most of these methods use WordNet. In contrast, we propose a simple approach to generate a high-coverage semantic orientation lexicon, which includes both individual words and multi-word expressions, using only a Roget-like thesaurus and a handful of affixes. Further, the lexicon has properties that support the Polyanna Hypothesis. Using the General Inquirer as gold standard, we show that our lexicon has 14 percentage points more correct entries than the leading WordNet-based high-coverage lexicon (SentiWordNet). In an extrinsic evaluation, we obtain significantly higher performance in determining phrase polarity using our thesaurus-based lexicon than with any other. Additionally, we explore the use of visualization techniques to gain insight into the our algorithm beyond the evaluations mentioned above. © 2009 ACL and AFNLP.

关键词： Thesauri

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Coping with training contamination in unsupervised distributional anomaly detection

Coping with training contamination in unsupervised distribut...

引用

Annual Conference on Information Sciences and Systems (CISS)

作者： Nash Borges Gerard G. L. Meyer Human Language Technology Center of Excellence Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA

In previous work, we presented several distributional approaches to anomaly detection for a speech activity detector by training a model on purely nominal data and estimating the divergence between it and other input. Here, we reformulate the problem in an unsupervised framework and allow for anomalous contamination of the training data. After noting the instability of Gaussian mixture models (GMMs) in this context, we focus on non-parametric methods using regularly binned histograms. While the performance of the log likelihood baseline suffered as the amount of contamination was increased, many of the distributional approaches were not affected. We found that the L 1 distance, chi 2 statistic, and information theory divergences consistently outperformed the other methods for a variety of contamination levels and test segment lengths.

关键词： Contamination speech Detectors Training data Context modeling Histograms Statistical analysis Statistical distributions Information theory Testing

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Multimodal floor control shift detection 09

Multimodal floor control shift detection

引用

International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interfaces, ICMI-MLMI'09

作者： Chen, Lei Harper, Mary P. ECE School Purdue University West Lafayette IN 47906 United States Princeton NJ 08541 United States UMIACS University of Maryland College Park MD 20472 United States Human Language Technology Center of Excellence Johns Hopkins Univ. Baltimore MD 21211 United States

ISBN: (纸本)9781605587721

Floor control is a scheme used by people to organize speaking turns in multi-party conversations. Identifying the floor control shifts is important for understanding a conversation's structure and would be helpful for more natural human computer interaction systems. Although people tend to use verbal and nonverbal cues for managing floor control shifts, only audio cues, e.g., lexical and prosodic cues, have been used in most previous investigations on speaking turn prediction. In this paper, we present a statistical model to automatically detect floor control shifts using both verbal and nonverbal cues. Our experimental results show that using a combination of verbal and nonverbal cues provides more accurate detection. Copyright 2009 ACM.

关键词： human computer interaction

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Arabic cross-document coreference detection

Arabic cross-document coreference detection

引用

Joint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and 4th International Joint Conference on Natural language processing of the AFNLP, ACL-IJCNLP 2009

作者： Sayeed, Asad Elsayed, Tamer Garera, Nikesh Alexander, David Xu, Tan Oard, Douglas W. Yarowsky, David Piatko, Christine Human Language Technology Center of Excellence Johns Hopkins University Baltimore MD United States Dept. of Computer Science University of Maryland College Park MD United States BBN Technologies Cambridge MA United States College of Information Studies University of Maryland College Park MD United States UMIACS University of Maryland College Park MD United States Dept. of Computer Science Johns Hopkins University Baltimore MD United States

ISBN: (纸本)9781617382581

We describe a set of techniques for Arabic cross-document coreference resolution. We compare a baseline system of exact mention string-matching to ones that include local mention context information as well as information from an existing machine translation system. It turns out that the machine translation-based technique outperforms the baseline, but local entity context similarity does not. This helps to point the way for future crossdocument coreference work in languages with few existing resources for the task. © 2009 ACL and AFNLP.

关键词： Machine translation

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Retrieval experiments at Morpho Challenge 2008

Retrieval experiments at Morpho Challenge 2008

引用

2008 Working Notes for CLEF Workshop, CLEF 2008 - Co-located with the 12th European Conference on Digital Libraries, ECDL 2008

作者： McNamee, Paul JHU Human Language Technology Center of Excellence United States

Morpho Challenge 2008 hosted an extrinsic evaluation of morphological analysis that explored whether unsupervised morphology induction could benefit information retrieval. This paper presents results in alternative methods for word normalization using test sets from the Cross-language Evaluation Forum (CLEF) ad-hoc collections. Preliminary results for the Morpho Challenge 2008 evaluation are consistent with these data. We found that: (1) rule-based stemming is effective in less morphologically complicated languages;(2) alternative methods for stemming such as unsupervised learning of morphemes and least common n-gram stemming are helpful;and, (3) full character n-gram indexing is the most effective form of tokenization in more morphologically complex languages.

关键词： Computational linguistics

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Pairwise document similarity in large collections with MapReduce 46

Pairwise document similarity in large collections with MapRe...

引用

46th Annual Meeting of the Association for Computational Linguistics: human language Technologies, ACL 2008

作者： Elsayed, Tamer Lin, Jimmy Oard, Douglas W. Human Language Technology Center of Excellence UMIACS Laboratory for Computational Linguistics and Information Processing University of Maryland College ParkMD20742 United States Department of Computer Science The iSchool College of Information Studies

This paper presents a MapReduce algorithm for computing pairwise document similarity in large document collections. MapReduce is an attractive framework because it allows us to decompose the inner products involved in computing document similarity into separate multiplication and summation stages in a way that is well matched to efficient disk access patterns across several machines. On a collection consisting of approximately 900,000 newswire articles, our algorithm exhibits linear growth in running time and space in terms of the number of documents. © 2008 Association for Computational Linguistics.

关键词： MapReduce

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Computing word-pair antonymy

Computing word-pair antonymy

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2008 Conference on Empirical Methods in Natural language processing, EMNLP 2008, Co-located with AMTA 2008 and the International Workshop on Spoken language Translation

作者： Mohammad, Saif Dorr, Bonnie Hirst, Graeme Laboratory for Computational Linguistics and Information Processing Institute for Advanced Computer Studies University of Maryland United States Computer Science Human Language Technology Center of Excellence United States Department of Computer Science University of Toronto Canada

Knowing the degree of antonymy between words has widespread applications in natural language processing. Manually-created lexicons have limited coverage and do not include most semantically contrasting word pairs. We present a new automatic and empirical measure of antonymy that combines corpus statistics with the structure of a published thesaurus. The approach is evaluated on a set of closest-opposite questions, obtaining a precision of over 80%. Along the way, we discuss what humans consider antonymous and how antonymy manifests itself in utterances. © 2008 Association for Computational Linguistics.

关键词： Natural language processing systems

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Computing word-pair antonymy 08

Computing word-pair antonymy

引用

Proceedings of the Conference on Empirical Methods in Natural language processing

作者： Saif Mohammad Bonnie Dorr Graeme Hirst University of Maryland Human Language Technology Center of Excellence University of Toronto

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Resolving personal names in email using context expansion

Resolving personal names in email using context expansion

引用

46th Annual Meeting of the Association for Computational Linguistics: human language Technologies, ACL-08: HLT

作者： Elsayed, Tamer Oard, Douglas W. Namata, Galileo Department of Computer Science Human Language Technology Center of Excellence University of Maryland College Park MD 20742 United States University of Maryland College Park MD 20742 United States

ISBN: (纸本)9781932432046

This paper describes a computational approach to resolving the true referent of a named mention of a person in the body of an email. A generative model of mention generation is used to guide mention resolution. Results on three relatively small collections indicate that the accuracy of this approach compares favorably to the best known techniques, and results on the full CMU Enron collection indicate that it scales well to larger collections. © 2008 Association for Computational Linguistics.

关键词： Electronic mail

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