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The proposed approach aims to mine a reduced set of effective association pattern rules for enhancing the online performance of web recommendations. We have incorporated the proposed approach into a personalized web recommender system known as AWARS. The performance of the proposed approach is evaluated based on the efficiency and the quality. In the efficiency evaluation, we measure the number of generated rules and the runtime for online recommendations. In the quality evaluation, we measure the quality of the recommendation service based on precision, satisfactory and applicability. This paper will discuss the proposed WUL\u2010based mining approach, and give the performance of the proposed approach in comparison with the Apriori\u2010based algorithms.<\/jats:p>","DOI":"10.1108\/17440080580000089","type":"journal-article","created":{"date-parts":[[2010,6,5]],"date-time":"2010-06-05T07:17:40Z","timestamp":1275722260000},"page":"137-146","source":"Crossref","is-referenced-by-count":5,"title":["A web usage lattice based mining approach for intelligent web personalization"],"prefix":"10.1108","volume":"1","author":[{"given":"Baoyao","family":"Zhou","sequence":"first","affiliation":[]},{"given":"Siu","family":"Cheung Hui","sequence":"additional","affiliation":[]},{"given":"Alvis C. 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