Semantic Relation’s Weight Determination on a Graph Based WordNet
Abstract
Determination of semantic relatedness between two textual items is one of the crucial phases in many Natural Language Processing applications. In this study, a new approach to lexicon based semantic relation determination methods was experienced using WordNet 3.0 and Men’s real-life similarity dataset. Men’s test collection was used for the determination of the relation weights and determined weights were used in semantic relatedness computation. RG65 similarity dataset was used for a benchmark of the proposed method and Spearman correlation 0.81 was gained, taking into account that retrieving the relations weight using a large scale dataset and testing them with another real-life dataset promises new perspectives to the determination of the relations weight and to the relatedness computation.
Keywords
Kaynakça
- Aguirre, E. and Soroa, A., 2009. Personalizing PageRank for Word Sense Disambiguation. Proceedings of the 12th conference of the European chapter of the Association for Computational Linguistics, March 2009, Athens, Greece, p. 34-41.
- Ahsan, M.G., Naghibzadeh, M. and Naeini, S.E.Y., 2014. Semantic similarity assessment of words using weighted WordNet, Int. J. Mach. Learn. & Cyber, 5 (3), 479-490, https://doi.org/10.1007/s13042-012-0135-3.
- Brin, S. and Page, L., 1998. The anatomy of a large-scale hypertextual web search engine. Computer Networks and ISDN Systems 30, 107-117.
- Bruni, E., Tran, N. K. and Baroni, M., 2014. Multimodal Distributional Semantics. Journal of Artificial Intelligence Research, 49, 1-47, https://doi.org/10.1613/jair.413.
- Fellbaum, C., 1998. WordNet: An Electronic Lexical Database. Cambridge, MA: MIT Press, 422p.
- Finkelstein, L., Gabrilovich, E., Matia,S., Y., Rivlin, E., Solan, Z., Wolfman, G. and Ruppin, E., 2001. Placing search in context: The concept revisited. In WWW ’01: Proceedings of the 10th international conference on World Wide Web, May 2001, Hong Hong, p. 406–414.
- Hirst, G. and St-Onge, D, 1998, Lexical chains as representations of context for the detection and correction of malapropisms, in WordNet: An Electronic Lexical Database, MITP, p. 305–332.
- Hughes, T. and Ramage, D., 2007. Lexical semantic relatedness with random graph walks. Proceedings of the Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, EMNLP–CoNLL, June 2007, Prague, Czech Republic, p.581–589.
- Kartsaklis D., Pilehvar M.T. and Collier N., 2018. Mapping Text to Knowledge Graph Entities using Multi-Sense LSTMs. EMNLP, Oct. 2018, Brussels, Belgium.
- Li, Y., Zuhair, A. B. and McLean, D., 2003. An approach for measuring semantic similarity between words using multiple information sources, IEEE Trans. Knowledge and Data Eng., 15 (4), 871-882.