Browsing by Author "ZEESHAN KHAN"

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    FREQUENT PATTERN MINING AND RECOMMENDATION SYTEM FOR ONLINE CLOTHING STORE
    (UMT, Lahore, 2018) ZEESHAN KHAN
    Data mining is manner of extracting useful facts from huge amount of scattered data. Frequent item set mining is largely used in financial, retail and telecommunication industry. A major problem for many organizations is to handle and analyze transactional data of their products and identify items which are sold together. Organizations need knowledge patterns to improve sales as well as customer satisfaction on the basis of past transactional data. This study is focusing on development of a recommender system for online clothing store based on market basket analysis. The system uses association rule mining to find frequent patterns for market basket analysis uses a hybrid filtering approach for recommendations. The proposed method is an intelligent and efficient approach towards finding frequent patterns, and recommends the products on the basis of past transactional data and the geographical situation of the customer. The work proposes a system which will allow the user to find the frequent patterns from the whole dataset using A priori a popular Data Mining algorithm. The system also enables the business to find frequent patterns out of the given patterns and for this problem the proposed system uses Targeted Patterns Involved Items Transaction Reduction Frequent Pattern Mining (TPIITR-FPMM). The other part of the system deals with the recommendations of the products to the customer who may belong to different cities of Pakistan. For this purpose the system uses hybrid filtering technique.