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VOC Summarization and Classification based on Sentence Understanding
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 Title & Authors
VOC Summarization and Classification based on Sentence Understanding
Kim, Moonjong; Lee, Jaean; Han, Kyouyeol; Ahn, Youngmin;
 
 Abstract
To attain an understanding of customers' opinions or demands regarding a companies' products or service, it is important to consider VOC (Voice of Customer) data; however, it is difficult to understand contexts from VOC because segmented and duplicate sentences and a variety of dialog contexts. In this article, POS (part of speech) and morphemes were selected as language resources due to their semantic importance regarding documents, and based on these, we defined an LSP (Lexico-Semantic-Pattern) to understand the structure and semantics of the sentences and extracted summary by key sentences; furthermore the LSP was introduced to connect the segmented sentences and remove any contextual repetition. We also defined the LSP by categories and classified the documents based on those categories that comprise the main sentences matched by LSP. In the experiment, we classified the VOC-data documents for the creation of a summarization before comparing the result with the previous methodologies.
 Keywords
summarization;text classification;sentence analysis;sentence understanding;VOC;
 Language
Korean
 Cited by
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