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Taming Social Tags: Computational Linguistic Analysis of Tags for Images in Museums
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Measuring Variability in Sentence Ordering for News Summarization
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CLiMB ToolKit: A Case Study of Iterative Evaluation in a Multidisciplinary Project
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CLiMB ToolKit: A Case Study of Iterative Evaluation in a Multidisciplinary Project ...
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Customization in a Unified Framework for Summarizing Medical Literature
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Similarity-based Multilingual Multi-Document Summarization ...
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Lexicalized Well-Founded Grammars: Learnability and Merging ...
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Inducing Constraint-based Grammars from a Small Semantic Treebank
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Inducing Constraint-based Grammars from a Small Semantic Treebank ...
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Abstract:
We present a relational learning framework for grammar induction that is able to learn meaning as well as syntax. We introduce a type of constraint-based grammar, lexicalized well-founded grammar (lwfg), and we prove that it can always be learned from a small set of semantically annotated examples, given a set of assumptions. The semantic representation chosen allows us to learn the constraints together with the grammar rules, as well as an ontology-based semantic interpretation. We performed a set of experiments showing that several fragments of natural language can be covered by a lwfg,and that it is possible to choose the representative examples heuristically, based on linguistic knowledge. ...
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Keyword:
Computer science; Information technology
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URL: https://academiccommons.columbia.edu/doi/10.7916/D84J0PKP https://dx.doi.org/10.7916/d84j0pkp
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Columbia’s Newsblaster: New Features and Future Directions
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Klavans, Judith L.; Barzilay, Regina; Nenkova, Ani. - : NAACL-Demonstrations '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: Demonstrations, 2003
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Combining linguistic and machine learning techniques for email summarization
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GIST-IT: Summarizing Email Using Linguistic Knowledge and Machine
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