BibSonomy publications for /user/diego_ma/WordNetWed Feb 03 05:45:59 CET 2010Jeju, KoreaProceedings of 2nd International Joint Conference on Natual Language Processing945--956Automatic Interpretation of Compound Nouns using {WordNet} Similarity2005compound_nouns WordNet Wed Sep 17 10:42:20 CEST 2008Proc. Fourth Global WordNet Conference (GWC'08)Using and Extending WordNet to Support Question-Answering2008entailment question_answering wordnet Over the last few years there has been increased research in automated question-answering from text, including questions whose answer is implied, rather than explicitly stated, in the text. WordNet has played a central role in many such systems (e.g., 21 of the 26 teams in the recent PASCAL RTE3 challenge used WordNet), and thus WordNet is being increasingly stretched to play more semantic tasks in applications. As part of our current research, we are exploring some of the new demands which question-answering places on WordNet, and how it might be further extended to meet them. In this paper, we present some of these new requirements, and some of the extensions that we are currently making to WordNet in response.Fri Dec 14 02:49:24 CET 2007Cambrige, MAWordNet: an electronic lexical databaseLanguage, Speech, and CommunicationWordNet: an electronic lexical database1998WordNet Fri Dec 14 02:47:56 CET 2007Talk given at IFIIntegration von GermaNet in EuroWordNet, eine multilinguale lexikalisch-semantische Datenbank1999talk_presentation WordNet Fri Dec 14 02:45:37 CET 2007Journal of Artificial Intelligence Research95-130Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language111998WordNet semantic_closeness This article presents a measure of semantic similarity in an IS-A taxonomy based on the notion of shared information content. Experimental evaluation against a benchmark set of human similarity judgments demonstrates that the measure performs better than the traditional edge-counting approach. The article presents algorithms that take advantage of taxonomic similarity in resolving syntactic and semantic ambiguity, along with experimental results demonstrating their effectiveness.Fri Dec 14 02:43:33 CET 2007Proc. COLING 2002Lexical Chains for Question Answering2002question_answering WordNet The paper presents a method for finding topically related words on an extended WordNet. By exploiting the information in the WordNet glosses, the connectivity between the synsets is dramatically increased. Topical relations expressed as lexical chains on extended WordNet improve the performance of a question answering system by increasing the document retrieval recall and by providing the much needed axioms that link question keywords with answers.Fri Dec 14 02:43:26 CET 2007International Journal of Lexicography4235-244Introduction to Wordnet: an on-line lexical database31990WordNet Fri Dec 14 02:42:57 CET 2007Proceedings of the NAACL 2001 Workshop on WordNet and Other Lexical Resources: Applications, Extensions and Customizations138-143The Informative Role of {WordNet} in Open-Domain Question Answering2001question_answering WordNet Finding information of interest from large text collections requires knowledge that goeas beyond the use of several lexical keywords. The WordNet linguistic database encodes massive semantic, morphologic and pragmatic knowledge. This paper explores the art of finding and using linguistic knowledge from WordNet for high-performance textual Question Answering.Fri Dec 14 02:42:18 CET 2007Communications of the ACM1145-48{CYC}, {WordNet}, and {EDR}: Critiques and Responses381995resources Cyc WordNet Authors Doug Lenat, George Miller, and Toshio Yokoi critique and defend one another's systems, ideas, and approaches to AI developmentsFri Dec 14 02:39:59 CET 2007Proc. SIGLEX 1999{WordNet} 2 -- A Morphologically and Semantically Enhanced Resource1999WordNet logical_forms This paper presents an on-going project intended to enhance WordNet morphologically and semantically. The motivation for this work steams from the current limitations of WordNet when used as a linguistic knowledge base. We envision a software tool that automatically parses the conceptual defining glosses, attributing part-of-speech tags and phrasal brackets. The nouns, verbs, adjectives and adverbs from every definition are linked to the corresponding synsets. This increases the connectivity between synsets allowing the retrieval or topically related concepts. Furthermore, the tool transforms the glosses, first into logical forms and then into semantic forms. Using derivational morphology new links are added between the synsets.Fri Dec 14 02:39:57 CET 2007Proc. LREC-2000Acquisition of Linguistic Patterns for Knowledge-Based Information Extraction2000inf_extraction WordNet In this paper we present a new method of automatic acquisition of linguistic patterns for Information Extraction, as implemented in the CICERO system. Our approach combines lexico-semantic information available from the WordNet database with collocating data extracted from training corpora. Due to the open-domain nature of the WordNet information and the immediate availability of large collections of texts, our method can be easily ported to open-domain Information Extraction.Fri Dec 14 02:39:13 CET 2007Conceptual Analysis of Lexical Taxonomies: The Case of {WordNet} Top-Level2001WordNet In this paper we propose an analysis and an upgrade of WordNet's top-level synset taxonomy. We briefly review WordNet and identify its main semantic limitations. Some principles from a forthcoming OntoClean methodology are applied to the ontological analysis of WordNet. A revised top-level taxonomy is proposed, which is meant to be more conceptually rigorous, cognitively transparent, and efficiently exploitable in several applications.Fri Dec 14 02:36:48 CET 2007Computational Linguistics113-47Evaluating WordNet-based Measures of Semantic Distance322006WordNet The quantification of lexical semantic relatedness has many applications in NLP, and many different measures have been proposed. We evaluate five of these measures, all of which use WordNet as their central resource, by comparing their performance in detecting and correcting real-word spelling errors. An information-content--based measure proposed by Jiang and Conrath is found superior to those proposed by Hirst and St-Onge, Leacock and Chodorow, Lin, and Resnik. In addition, we explain why distributional similarity is not an adequate proxy for lexical semantic relatedness.