Exploiting links in WordNet hierarchy for word sense disambiguation of nouns

Authors:
S. G. Kolte;S. G. Bhirud
Affiliations:
K. J. Somaiya Polytechnic, Vidyavihar, Mumbai;Veermata Jijabai Technological Institute, Matunga, Mumbai
Venue:
Proceedings of the International Conference on Advances in Computing, Communication and Control
Year:
2009

Citing 7
Cited 0

Using WordNet to disambiguate word senses for text retrieval

SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Word sense disambiguation for free-text indexing using a massive semantic network

CIKM '93 Proceedings of the second international conference on Information and knowledge management
Automatic sense disambiguation using machine readable dictionaries: how to tell a pine cone from an ice cream cone

SIGDOC '86 Proceedings of the 5th annual international conference on Systems documentation
Topical clustering of MRD senses based on information retrieval techniques

Computational Linguistics - Special issue on word sense disambiguation
Word sense disambiguation using Conceptual Density

COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Lexical disambiguation using simulated annealing

HLT '91 Proceedings of the workshop on Speech and Natural Language
Word Sense Disambiguation: Algorithms and Applications (Text, Speech and Language Technology)

Word Sense Disambiguation: Algorithms and Applications (Text, Speech and Language Technology)

Quantified Score

Hi-index	0.00

Visualization

Abstract

Word Sense Disambiguation is the most critical issue in natural language processing. Although it has been addressed by many researchers, no satisfactory results are reported. Rule based systems alone can not handle this issue due to ambiguous nature of the natural language. Knowledge-based systems are therefore essential to find the intended sense of a word form. Machine readable dictionaries have been widely used in word sense disambiguation. The problem with this approach is that the dictionary entries for the target words are very short. WordNet is the most developed and widely used lexical database for English. The entries are always updated and many tools are available to access the database on all sorts of platforms. The WordNet database can be converted in MySQL format and we have modified it as per our requirement. Sense's definitions of the specific word, "Synset" definitions, the "Hypernymy" relation, and definitions of the context features (words in the same sentence) are retrieved from the WordNet database and used as an input of our Disambiguation algorithm.