Individual Project

Knowledge Management is crucial for most organizations. Companies maintain their core capacities and advantages through effectively utilizing their knowledge assets. Yet, many KMS nowadays still serve as only data repositories. The data processing techniques of these systems are not sophisticated enough to help user filter the irrelevant information resources and recommend those which match users' expectations. Knowledge Management Systems (KMS) were developed as solutions to the problem.

I propose a recommender system as a supplement to the existing current KMSs. The recommender system improves the KMS in two ways: 1) It helps the KMS to push the right information to the right people at the right time. To achieve the goal, the recommender system presents a ranked search results based on the relevancy and the quality of the document. 2) It helps users to identify other employees with the knowledge to solve their problems.