A Knowledge Mining Approach to Document Classification

Andreas Riel (1) , Pawinee Boonyasopon (1)

1 G-SCOP_CPP - Conception Produit Process

In the information age, there exists a huge amount of electronic data and information worldwide. A great challenge is how to exploit those information and knowledge resources and to turn them into useful knowledge available to concerned people, since the value of knowledge increases when people can share and capitalize on it. Thus approaches that can help researchers to benefit from existing hidden knowledge are needed. To this aim, tools that can extract relevant and useful knowledge are required. Text Mining is considered to be a key idea in order to help researchers to be able to extract explicit or implicit knowledge from unstructured data which is mainly in text written form. This paper presents the application of a text analysis tool that is used to mine knowledge by analyzing electronic text written documents in order to categorize different knowledge domains, to identify significant terms related to the documents and clusters of related documents, to identify unknown information hidden in these documents, find the relationships among them, and to visualize clusters of related topics and documents.

Mots clés: Knowledge Mining; Text Mining; Knowledge Sharing; Document Classification

Domaines: Autre; Traitement du texte et du document

Andreas Riel, Pawinee Boonyasopon. A Knowledge Mining Approach to Document Classification. Asian International Journal of Science and Technology in Production and Manufacturing Engineering, 2009, 2 (3), pp.1-10. ⟨hal-00528250⟩