Design of Search Engine Considering Top k High Utility Item Set (HUI) Mining and Defining the Recommendation and Point of Interest (POI)

Abstract

Frequent Item sets discovery mechanism of items set that are frequently purchased together by customer. High Utility Item sets (HUIs) deals with discovery of an item set with high utility such as streaming analysis, market analysis, mobile computing and biomedicine. HUIs consider with particular attribute of the item set. HUIs mining is defined as qualitative representation of user preferences. The primary goal of mining is to discover hidden patterns and unexpected trends in data set with HUI and the secondary goal is to discover Top-k results. Point of Interest (POI) is to provide personalized recommendation of particular aspects such as restaurants, movie theaters. Recommendation depends upon user previous interest or previous search options. HUIs mining identifies item sets where its attribute satisfies threshold. According to the threshold, items categorized as High Utility Item sets and Low Utility item sets. Resulting candidate item sets further undergoes pruning techniques so as to reduce no. of candidate item set considering. Efficient framework can be designed for mining Top-k HUIs set where k is no. of HUIs to be mined and defining the recommendation and POI. HUI mining is used to find Top-k results to enhance decision making process. HUIs mining is useful for building powerful search engines to display Top-k results. It has many application like market analysis, stream analysis and biometric. Index Terms—Utility mining, high utility item sets, high utility item set mining, top-k, pattern mining, parallel mining, top-k high utility item set mining, Data mining ,frequent item set, transactional database.