Text Mining

The aim of the text mining project is to research technologies to discover useful knowledge from enormous collections of documents, and to develop a system to provide this knowledge and to support the user's decisions. Usually data mining technologies mine knowledge from data with well-formed schemes such as relational tables. But, text data don't have such scheme, and information is described freely in the documents. Therefore, we focus on Natural Language Processing(NLP) technologies to extract such information. Using NLP technologies, documents are transformed into a collection of concepts, described using terms discovered in the text.

Usually, "text mining" is used to indicate a text search technique. But, we think of text mining as having more functions. Text mining technologies extract more information than just picking up keywords from texts: facts, author's intentions, their expectations, and their claims. This knowledge is helpful to many applied tasks such as marketing, trend analysis, claim processing, generating FAQ(frequently asked questions), and so on.

In this project, we provide two text mining solutions. One solution is for CRM which extracts useful information from call center logs for marketing strategy and so on. The other solution is for life science which helps find novel knowledge from huge number of biomedical documents.