Boolean Based Mining Algorithm for Pattern Discovery Based on Human Interaction
Ramanayagam S1, Raja K2, Kannan K3

1Ramanayagam S, Research and Development Centre, Bharathiar University, Coimbatore, India,
2Raja K, Department of Computer Science Engineering, Dhaanish Ahmed College of Engineering, Chennai, India
3Kannan K, Department of Information Technology, AdhiParasakthi College of Engineering, Kalavai, India.

Manuscript received on 27 June 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 2827-2831 | Volume-8 Issue-9, July 2019 | Retrieval Number: I8666078919/19©BEIESP | DOI: 10.35940/ijitee.I8666.078919

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Abstract: Mining is a process that provides useful information on surfing and access pattern information based on capturing the behaviour of the user. Semantic knowledge helps to understand how the users will interact with the system. In this paper, we propose a Boolean based APriori Pattern (APP) algorithm to discover pattern based on human interaction using behavioural analysis. In the process of data mining, we have used a Boolean expression that helps to determine the pattern discovery based on the use of frequent pattern by applying association rules. The behavioural analysis is proposed based on the classification of ideas based on comments concerning positive opinion /contrary opinion during human interaction in the practical scenarios. The behavioural analysis is represented as a tree hierarchy where tree based mining is performed by the tree construction and interaction of flow patterns i.e., frequent patterns. The study shows that the successful pattern can be extracted based on the behavioural analysis of human interaction such as frequent pattern, flow interaction and relationships between the interactions.
Keywords: Semantic Knowledge, Boolean, Mining, Frequent Pattern, Human Interaction, Behavioural.

Scope of the Article: Human Computer Interactions