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Artificial Intelligence - Special volume on natural language processing
Selection and information: a class-based approach to lexical relationships
Selection and information: a class-based approach to lexical relationships
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An Introduction to Variational Methods for Graphical Models
Machine Learning
Text Classification from Labeled and Unlabeled Documents using EM
Machine Learning - Special issue on information retrieval
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The Journal of Machine Learning Research
Automatic verb classification based on statistical distributions of argument structure
Computational Linguistics
Discovery of inference rules for question-answering
Natural Language Engineering
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
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Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Probability and Computing: Randomized Algorithms and Probabilistic Analysis
Probability and Computing: Randomized Algorithms and Probabilistic Analysis
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Computational Linguistics
Exploring evidence for shallow parsing
ConLL '01 Proceedings of the 2001 workshop on Computational Natural Language Learning - Volume 7
Robust, applied morphological generation
INLG '00 Proceedings of the first international conference on Natural language generation - Volume 14
Topic modeling: beyond bag-of-words
ICML '06 Proceedings of the 23rd international conference on Machine learning
Similarity of Semantic Relations
Computational Linguistics
Discovering asymmetric entailment relations between verbs using selectional preferences
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Event extraction in a plot advice agent
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Recognizing contextual polarity in phrase-level sentiment analysis
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Bidirectional inference with the easiest-first strategy for tagging sequence data
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Adding predicate argument structure to the Penn TreeBank
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Weighted Graph Cuts without Eigenvectors A Multilevel Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Topic modeling with network regularization
Proceedings of the 17th international conference on World Wide Web
A general feature space for automatic verb classification
Natural Language Engineering
Mixed Membership Stochastic Blockmodels
The Journal of Machine Learning Research
Classifying temporal relations between events
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Mining the web for reciprocal relationships
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning
Methods for domain-independent information extraction from the web: an experimental comparison
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Learning systems of concepts with an infinite relational model
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Jointly combining implicit constraints improves temporal ordering
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
NAACL-Short '06 Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers
SemEval-2007 task 15: TempEval temporal relation identification
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
SemEval-2010 task 13: evaluating events, time expressions, and temporal relations (TempEval-2)
DEW '09 Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions
Unsupervised learning of narrative schemas and their participants
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
Cross-cultural analysis of blogs and forums with mixed-collection topic models
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
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Reciprocity is a pervasive concept that plays an important role in governing people's behavior, judgments, and thus their social interactions. In this paper we present an analysis of the concept of reciprocity as expressed in English and a way to model it. At a larger structural level the reciprocity model will induce representations and clusters of relations between interpersonal verbs. In particular, we introduce an algorithm that semi-automatically discovers patterns encoding reciprocity based on a set of simple yet effective pronoun templates. Using the most frequently occurring patterns we queried the web and extracted 13,443 reciprocal instances, which represent a broad-coverage resource. Unsupervised clustering procedures are performed to generate meaningful semantic clusters of reciprocal instances. We also present several extensions (along with observations) to these models that incorporate meta-attributes like the verbs' affective value, identify gender differences between participants, consider the textual context of the instances, and automatically discover verbs with certain presuppositions. The pattern discovery procedure yields an accuracy of 97 per cent, while the clustering procedures ??? clustering with pairwise membership and clustering with transitions ??? indicate accuracies of 91 per cent and 64 per cent, respectively. Our affective value clustering can predict an unknown verb's affective value (positive, negative, or neutral) with 51 per cent accuracy, while it can discriminate between positive and negative values with 68 per cent accuracy. The presupposition discovery procedure yields an accuracy of 97 per cent.