M. Oussalah, M. Väisänen and E. Gilman, "On Wordsense Disambiguation through Morphological Transformation and Semantic Distance and Domain Link Knowledge," 2018 IEEE International Conference on Information Reuse and Integration (IRI), Salt Lake City, UT, 2018, pp. 117-121, https://doi.org/10.1109/IRI.2018.00024
On wordsense disambiguation through morphological transformation and semantic distance and domain link knowledge
|Author:||Oussalah, M.1; Väisänen, M.1; Gilman, E.1|
1Centre for Ubiquitous Computing, Faculty of Information technology, University of Oulu, Oulu, Finland
|Online Access:||PDF Full Text (PDF, 0.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2020042119548
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2020-04-21
Despite the advances in information processing systems, word-sense disambiguation tasks are far to be satisfactory as testified by numerous limitations of current translation systems and text inference systems. This paper attempts to investigate new techniques in knowledge based word-sense disambiguation field. First, by exploring the WordNet lexical database and part-of-speech conversion through the established CatVar database that translates all non-noun words into their noun counterparts, and following the spirit of Lesk’s disambiguation algorithm, a new disambiguation algorithm that maximizes the overall semantic similarity in the sense of Wu and Palmer measure between each sense of the target word and synsets of words of the context, is established. Second, motivated by the existence of WordNet domains for individual synsets, an overlapping based approach that quantifies the set intersection of synset domains, if not empty, or the hierarchy structure of the domains links through a simple path-length measure is put forward. Third, instead of exploring the whole set of words involved in the context, a selective approach that uses syntactic feature as outputted by Stanford Parser and a fixed length windowing is developed. The developed algorithms are evaluated according to two commonly employed dataset where a clear improvement to the baseline algorithm has been acknowledged.
|Pages:||117 - 121|
2018 IEEE International Conference on Information Reuse and Integration (IRI)
IEEE International Conference on Information Reuse and Integration
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
113 Computer and information sciences
213 Electronic, automation and communications engineering, electronics
This work is partially supported by EU Marie Skodowska- Curie grant No 645706 and EU grant 770469-Cutler.
|EU Grant Number:||
(770469) CUTLER - Coastal Urban developmenT through the LEnses of Resiliency
© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.