Abstract: One of the important types of information on the Web is the opinions expressed in the user generated content, e.g., customer reviews of products, forum posts, and blogs. In this paper, we focus on customer reviews of products. In particular, we study the problem of determining the semantic orientations (positive, negative or neutral) of opinions expressed on product features in reviews. This problem has many applications, e.g., opinion mining, summarization and search. Here weutilize a list of opinion words(also called opinion lexicon) for the purpose. Opinion words are words that express desirable (e.g., great, amazing, etc.) or undesirable (e.g., bad, poor, etc.) states. Sometime customers writes the wrong spellings for the product property so we solve this problem here by using fuzzy string searching. Approximate string matching (often colloquially referred to as fuzzy string searching) is the technique of finding strings that match a pattern approximately (rather than exactly).

Keywords: opinion mining, sentiment analysis, Fuzzy String Searching, Levenshtein distance, Semantic orientation.