Using Domain-Specific Knowledge to Classify E-negotiations
نویسندگان
چکیده
Texts exchanged in business-related Computer-Mediated Communication, or CMC, differ from texts exchanged in other business situations. CMC data have a high concentration of non-standard textual features. The fast-growing amount of business CMC data offers opportunities for the application of statistical Natural Language Processing and Machine Learning methods, especially for text-classification purposes. We suggest a domain-specific text representation that helps avoid the negative effect of the non-standard text features. We report a variety of classification results that use this representation. We also build a statistical language model for the data and present its results. This is the first study on both statistical modeling of such data and their classification solely through text representation.
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