Abstract
The objective of association rule mining is to mine interesting relationships, frequent patterns, associations between set of objects in the transaction database. In this paper, association rule is constructed from the proposed rule mining algorithm. Efficiency-based association rule mining algorithm is used to generate patterns and Rule Construction algorithm is used to form association among the generated patterns. This paper aims at applying crime dataset, from which frequent items are generated and association made among the frequent item set. It also compares the performance with other existing rule mining algorithm. The algorithm proposed in this paper overcomes the drawbacks of the existing algorithm and proves the efficiency in minimizing the execution time. Synthetic and real datasets are applied with the rule mining algorithm to check the efficiency and it proves the results through experimental analysis.
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Usha, D., Rameshkumar, K., Baiju, B.V. (2019). Association Rule Construction from Crime Pattern Through Novelty Approach. In: Peter, J., Alavi, A., Javadi, B. (eds) Advances in Big Data and Cloud Computing. Advances in Intelligent Systems and Computing, vol 750. Springer, Singapore. https://doi.org/10.1007/978-981-13-1882-5_22
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DOI: https://doi.org/10.1007/978-981-13-1882-5_22
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