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Community detection is an important task for mining the structure and function of complex networks. Many pervious approaches are difficult to detect communities with arbitrary size and shape, and are unable to identify hubs and outliers. A recently proposed network clustering algorithm, SCAN, is effective and can overcome this difficulty. However, it(More)
An implementation of data preprocessing system for Web usage mining and the details of algorithm for path completion are presented. After user session identification, the missing pages in user access paths are appended by using the referer-based method which is an effective solution to the problems introduced by using proxy servers and local caching. The(More)
In this paper an attempt has been made to explore the possibility of the usage of artificial neural networks as automated test oracle. Automated test oracle includes capabilities to generate expected output and compare it with actual output automatically. It is important for automated software testing. But there are very few techniques to implement it. In(More)
This paper defines a new distance based on the improved Levenshtein distance with the tolerance relation for incomplete nominal data, and a new similarity strategy for incomplete numerical data. Additionally, by these two dissimilarity measures, a new distance, which measures the dissimilarity of objects with nominal and numerical attributes, is(More)
Test data generation is very labor-intensive and expensive in software testing. The automation of test process can achieve significant reductions in the cost of software development. Combining the parallel search ability of the adaptive genetic algorithm (aGA) with the controllable jumping property of simulated annealing (SA), a kind of effective hybrid(More)