الفهرس 
Title : Enhanced clustering for textual case-based reasoning
AbstractOnly 14 pages are availabe for public view
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Abstract
As a result of the rapid development in the means of communication and storage, the sheer amount of textual data that becomes larger every day.The main objective of the Textual Case-Based Reasoning (TCBR) is to benefit from the knowledge inside these text data to introduce solutions for the future problems. For this reason, TCBR sys- tems must intelligently detect the latent knowledge in the data and provide successful solutions to enormous requests from large number of users in a timely manner.That is making TCBR a challenging problem for several reasons, one of which because a single case may consists of different topics and complex linguistic terms, and the other is related to the efficiency and accuracy of the used Information Retrieval (IR) process itself. Many efforts have been made to enhance the retrieval process in TCBR using clus- tering and feature selection methods. SOPHIA (SOPHisticated Information Analysis) approach is one of the most successful efforts which is characterized by its ability to work without the domain of knowledge or language dependency. SOPHIA is based on the conditional probability, which facilitates an advanced Knowledge Discovery (KD) framework for case-based retrieval