Abstract
The contents generated by the users on the Web play a vital role for researchers to extract knowledge from these contents. Users write their views by making comparison between two or more than two features in a product domain. Extracting these reviews from the Web helps in improving the business from competitors. In this paper, a method to extract the comparative sentences from the text documents using a rule-based shallow parser is proposed. A shallow parser holds a nonoverlapping area of text and allows extracting the part of the text based on the given rule or grammar. In order to identify and classify comparatives from text documents various rules were generated. The proposed technique is divided into two tasks: first, obtain the rules to identify the comparative sentences from various text documents, and second, classify the text documents into different categories of comparatives.
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Saritha, S.K., Pateriya, R.K. (2016). Rule-Based Shallow Parsing to Identify Comparative Sentences from Text Documents. In: Shetty, N., Prasad, N., Nalini, N. (eds) Emerging Research in Computing, Information, Communication and Applications . Springer, Singapore. https://doi.org/10.1007/978-981-10-0287-8_33
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DOI: https://doi.org/10.1007/978-981-10-0287-8_33
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