Measuring the semantic similarity between words is an important component in various tasks on the web are relation extraction, community mining, document clustering, and automatic metadata extraction.The usefulness of semantic similarity measures in these applications, accurately measuring semantic similarity between two words remains a challenging task. The project proposes an empirical method to estimate semantic similarity using page counts and text snippets retrieved from a web search engine for two words. Specifically, it defines various word co-occurrence measures using page counts and integrates those with lexical patterns extracted from text snippets. To identify the various semantic relations that exist between two given words, the project proposes a novel pattern extraction.
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