Modified Random Walk Algorithm to Improve the Efficiency of Word Sense Disambiguation (WSD) (International Journal of Engineering and Computer Science, 2017)
Natural language processing (NLP) is a field in computer science, artificial intelligence and the linguistics which mainly concentrates on the interactions between human languages (natural language) and the computer. One of the main challenges in NLP is ambiguity. Every language is ambiguous in nature, in the way that one word has multiple meaning and multiple words have same meaning. The ambiguities are generally categorized into two groups: lexical and structural ambiguities. Lexical ambiguity arises where there are two or more possible meaning for a single word. Structural ambiguities appear when a given sentence is interpreted in more than one way due to ambiguous sentence structure. Word Sense Disambiguation (WSD) is defined as the task of finding the correct sense of a word in a specific context. This paper presents our preliminary work towards building WSD system by constructing a corpus. We include a detailed analysis of the factor that affects the WSD algorithm and propose a modified algorithm based on random walk algorithm and compare the working of each of these algorithms