Abstract Association rule mining aims to extract interesting correlations, frequent patterns, associations among sets of items 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... Association rule mining aims to extract interesting correlations, frequent patterns, associations among sets of items 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. Read More Read Less

Abstract The Eagle expresses of Cloud computing plays a pivotal role in the development of Technology. The Technology momentum gaining Cloud System environment across the emerging Computational Intelligence as artificial intelligence in IOTs. Cloud Computing playing a pivotal role in providing the Optimized algorithms for the issues in cloud computing which are the global challenges. The problem aims to solve in... The Eagle expresses of Cloud computing plays a pivotal role in the development of Technology. The Technology momentum gaining Cloud System environment across the emerging Computational Intelligence as artificial intelligence in IOTs. Cloud Computing playing a pivotal role in providing the Optimized algorithms for the issues in cloud computing which are the global challenges. The problem aims to solve in such a way that it will provide an optimized solution. Among all these research areas the works are developing at a rapid speed. The rapid vision, models and challenges for efficient optimization of resource in cloud computing world. The key role of allocating these efficient resources and making the algorithms for its time and cost optimization keeping in consideration of its quality of services and characteristics. These both are effecting the performance of these techniques is a major drawback due to low accuracy and large computational complexity of the algorithms. Therefore the concept of fuzzy system is playing a pivotal role in designing such strategies in which it makes use of the concept Fuzzy sets, Fuzzy logic and reasoning, Fuzzy controllers, Rough sets, etc. As per the scenario the approach of the research is based on technology acceptance model (TAM) and the Rough Set Theory (RST). RST a great method for making a large difference in qualitative analysis situations. It’s a technique to found the knowledge discovery and handle the problems such as inductive reasoning, automatic classification, pattern recognition, learning algorithms, and data reduction. The rough set theory is the new method in cloud service selection so that the best services to provide for cloud users and efficient service improvement for cloud providers. Read More Read Less

Abstract Efficient representation of packet classifiers has become a significant challenge due to the rapid growth of data stored and processed in the forwarding, or routing, tables. In our work we propose two algorithms for reducing the size of forwarding tables both in length and width by the deletion of redundant bits and unreachable rules based on FCA analysis. We consider... Efficient representation of packet classifiers has become a significant challenge due to the rapid growth of data stored and processed in the forwarding, or routing, tables. In our work we propose two algorithms for reducing the size of forwarding tables both in length and width by the deletion of redundant bits and unreachable rules based on FCA analysis. We consider the task of transferring the forwarding packet to the correct destination as the task of multinomial classification. Thus, the process of reducing the forwarding table size corresponds to feature selection procedure with slight modifications. The presented techniques are based on closed descriptions and decision trees. The main challenge in applying decision trees to the task is processing the overlapping rules. To overcome this challenge we propose to employ concept-based hypotheses to delete unreachable actions assigned to the overlapping rules. The experiments were performed on data generated by the ClassBench software. The proposed approach results in significant decrease in bits in the forwarding tables as features. Read More Read Less