An Analysis of User Behavior using Closed Set of Agglomerative Approach with GRC Constraints
Amit Kumar Chouksey1, Mayank Namdev2
1Amit Kumar Chouksey, Sagar Institute of Research & Technology (SIRT), Bhopal (Madhya Pradesh), India.
2Prof. Mayank Namdev, Sagar Institute of Research & Technology (SIRT), Bhopal (Madhya Pradesh), India.
Manuscript received on 10 December 2017 | Revised Manuscript received on 18 December 2017 | Manuscript Published on 30 December 2017 | PP: 168-170 | Volume-7 Issue-2, December 2017 | Retrieval Number: B5272127217/17©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In the current scenario every Organization need to understand their customers’ behavior, preferences and future needs which depend upon past behavior. Web Usage Mining is an active research area in which customers session clustering is done to find out the customer’s activities. It investigates the problem of mining frequent pattern and especially focuses on reducing the number of rules using closed pattern technique. It also reduce scans the size of the database using Agglomerative clustering technique using partial database scan. It is perform by Profile based Closed Sequential Pattern Mining with Agglomerative Clustering. It searches the next request page in advance using only partial web data not in whole web data. There is an advantage to no need take input as number of cluster. So it utilized a personalized weighted recommendation system based on user’s interest with less execution time.
Keywords: Web Usage Mining, Prefix Span, Gap, Recency, Compactness, Data Stream, Closed Pattern, Data Mining, Personalization, Sequential Pattern Mining, Web Services, Agglomerative Clustering
Scope of the Article: Clustering