Summary of the paper

Title Extracting Lexico-conceptual Knowledge for Developing Persian WordNet
Authors Mehrnoush Shamsfard, Hakimeh Fadaei and Elham Fekri
Abstract Semantic lexicons and lexical ontologies are some major resources in natural language processing. Developing such resources are time consuming tasks for which some automatic methods are proposed. This paper describes some methods used in semi-automatic development of FarsNet; a lexical ontology for the Persian language. FarsNet includes the Persian WordNet with more than 10000 synsets of nouns, verbs and adjectives. In this paper we discuss extraction of lexico-conceptual relations such as synonymy, antonymy, hyperonymy, hyponymy, meronymy, holonymy and other lexical or conceptual relations between words and concepts (synsets) from Persian resources. Relations are extracted from different resources like web, corpora, Wikipedia, Wiktionary, dictionaries and WordNet. In the system presented in this paper a variety of approaches are applied in the task of relation extraction to extract ladled or unlabeled relations. They exploit the texts, structures, hyperlinks and statistics of web documents as well as the relations of English WordNet and entries of mono and bi-lingual dictionaries.
Topics Knowledge Discovery/Representation, Ontologies, Text mining
Full paper Extracting Lexico-conceptual Knowledge for Developing Persian WordNet
Slides -
Bibtex @InProceedings{SHAMSFARD10.784,
  author = {Mehrnoush Shamsfard and Hakimeh Fadaei and Elham Fekri},
  title = {Extracting Lexico-conceptual Knowledge for Developing Persian WordNet},
  booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)},
  year = {2010},
  month = {may},
  date = {19-21},
  address = {Valletta, Malta},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis and Mike Rosner and Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-6-7},
  language = {english}
Powered by ELDA © 2010 ELDA/ELRA