Expert Search based Knowledge Sharing System for Collaborative Environment

In collaborative environment (CE) multiple members work together to achieve a common goal. But to find person/source that has most relevant information is a challenging part as the information requirement varies from task to task. Today, people are working in a collaborative environment to explore the ever increasing data and have new insights for knowledge sharing. Analyzing these needs we have proposed a system that finds the most appropriate and relevant documents based on the search query. In this system relevancy of document is supported by expert search method. In expert search, various aspects such as author name, hit count (number of downloads) of document, time span of hit count and last hit to that document are considered and clustering of retrieved results with meaningful cluster labels are identified to find whether a search term is used in the intended sense in that document. In this system, documents uploaded by members are analyzed. After analysis, indexing of documents is done. Further based on search query documents are retrieved and labeled clusters of documents are formed. Finally expert search is applied over mined results. This system helps in getting exact knowledge with quick response and repeating efforts for finding same information can be avoided with efficient time utilization. The performance of proposed system is evaluated with respect to response time of system. Thus, the effective use of knowledge sharing (data/information) is achieved with the Expert Search for time efficient systems.