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Conference Paper  · June 2015 with159 Reads
DOI 10.1007/978-3-319-19581-0_18
Abstract
The problem of classifying sentences into various categories, arises frequently in text mining applications. One of the most important categorization of sentences observed in product reviews, movie reviews, blogs, customer feedbacks is-Suggestions, Appreciations and Complaints. We observed that the document classification techniques do not perform well for these three non-topical sentence classes. We propose to solve this problem using a supervised approach based on Dependency-based Word Subsequence Kernel and its variations. We compare the performance of our approach with the state-of-the-art short text classification techniques on 2 different datasets-Performance Appraisal comments and Product Reviews.
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    The problem of classifying sentences into various categories, arises frequently in text mining applications. One of the most important categorization of sentences observed in product reviews, movie reviews, blogs, customer feedbacks is - Suggestions, Appreciations and Complaints. We observed that the document classification techniques do not perform well for these three non-topical sentence... [Show full abstract]
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      We propose a Label Propagation based algorithm for weakly supervised text classification. We construct a graph where each document is represented by a node and edge weights represent similarities among the documents. Additionally, we discover underlying topics using Latent Dirichlet Allocation (LDA) and enrich the document graph by including the topics in the form of additional nodes. The edge... [Show full abstract]
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