Author : Khanapure V.M and Chirchi V.R

World Wide Web is the most useful source of information. A search engine can support only the initial stages of the search process. But, most of the search engines are keyword-based and are not much useful within a Web site to help the user to identify his preferred service. For this purpose, many companies use case-based systems to improve customer service quality. These systems face two challenges: 1) Case retrieval measures: case-based systems use traditional keyword-matching-based ranking schemes for case retrieval and have difficulty to capture the semantic meanings of cases and 2) Result representation: case-based systems return a list of past cases ranked by their relevance to a new request, and customers go through the list and examine the cases one by one to identify their desired cases. The objective of this research is to address these challenges, we develop iAssist – an Intelligent Assistance system, to automatically find problem solution patterns from the past interactions between customers and representatives.

Keywords: Semantic similarity, Symmetric non-negative matrix factorization, Multi-document summarization

Article published in International Journal of Current  Engineering  and Technology, Vol.4,No.3 (June- 2014)