Publication Type:

Conference Paper

Source:

WCI '15 Proceedings of the Third International Symposium on Women in Computing and Informatics, https://dl.acm.org/citation.cfm?id=2791426, Kochi, India (2015)

URL:

https://dl.acm.org/citation.cfm?id=2791426

Abstract:

The aspects of Artificial Intelligence and statistics such as Text mining, Data Mining can provide solutions to the area of concept mining. It provides powerful insights into the meaning and documents similarity without exploiting the semantics of the terms or phrases in the document. Our work determines the similarity of documents using semantic processing namely Word Sense Disambiguation by annotating the senses of the words in the documents and then performs traditional PageRank algorithm over it. The Algorithm ranks the possible senses and finds the correct sense according to the context. Our paper proposes the method of disambiguating the ambiguous words in order to find the document similarity. Moreover it is compared with the cosine similarity approach, which is frequently used to determine similarity between two documents to prove the accuracy of our work.

Cite this Research Publication

G. Veena and B. U, U. Sree Veni, “Improving the Accuracy of Document Similarity Approach using Word Sense Disambiguation”, in WCI '15 Proceedings of the Third International Symposium on Women in Computing and Informatics, Kochi, India, 2015.