Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Little words can make a big difference for text classification
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Context-sensitive learning methods for text categorization
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Exploiting clustering and phrases for context-based information retrieval
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Predictive data mining: a practical guide
Predictive data mining: a practical guide
Information retrieval algorithms: a survey
SODA '97 Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms
Computer Evaluation of Indexing and Text Processing
Journal of the ACM (JACM)
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In this paper we lay the necessary groundwork towards Quality Control in Customer Relationship Management, using free text customer feedback as the only source of data. In a scheme that follows the general principles of Case-Based Reasoning, dubbed here Case-Based Free Text Evaluation, a small subset of documents with customer comments is evaluated by human experts to obtain customer satisfaction ratings. The ratings of the remaining documents are estimated automatically. Now the entire document collection can be resampled to generate control charts that monitor customer satisfaction. As an illustration of this framework we are using viewers' comments submitted to the Internet Movie Database (IMDb) Web site after they watched a recent popular film.