ENHANCING BUSINESS PROCESS THROUGH RECOMMENDATION SYSTEM BASED ON RANKING AND QUERY REFORMULATION

Abstract

In Business process data mining and knowledge discovery plays a vital role which is more difficult to process due to the availability and enhancing nature of data every day. There is a gap between what the user wants and what the system perceives as needed by the user. One of the ways to enrich business is to personalize the websites for each user by understanding their need, interest and behavior. The main challenge is information overloading and user dynamic nature. Even for a sample of small content availability in the domain, the mismatch is significant. Information retrieval research has shown over the years that the focus of the users is over a short and limited number of results. Getting the accuracy of the results is thus a significant need. Recommendation systems for Business have focused on the match between the user and the content through methods that focus on personal profiles, server ranking and user query processing. This is the focus of this paper where authors propose. This model uses the advances in information retrieval research and leverages the basic pedagogical models. The experimental results have shown promise and thrown up some interesting challenges for the future.