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With the rapid growth of service volumes and types, discovering services in an efficient and accurate manner has become a significant challenge in service computing. Service clustering is an important technology to improve the efficiency of service discovery. In this paper, we propose a new service clustering approach, which starts from service documents and is based on the functional semantics of...
We always use CAPTCHA(Completely Automated Public Turing test to Tell Computers and Humans Apart) to prevent automated bot for data entry. Although there are various kinds of CAPTCHAs, text-based scheme is still applied most widely, because it is one of the most convenient and user-friendly way for daily user [1]. The fact is that segmentations of different types of CAPTCHAs are not always the same,...
CAPTCHA (Completely Automated Public Turing test to Tell Computers and Humans Apart) is almost everywhere in data entry due to automated scripts like bots. Nowadays, text-based scheme is still applied most widely, which typically need the users to answer questions regarding recognition task. In particular, the segmentations of different types of CAPTCHAs are not always the same. As so far, there isn't...
With the increasingly widespread adoption of cloud computing and tenants' growing needs for large-scale data processing, cluster scheduling frameworks (e.g. MapReduce, Spark, etc.) have emerged as important programming models that works for distributed and parallel computing on cloud systems. While several recent researches proposed some solutions to optimize the MapReduce-like scheduler, they hardly...
Outlier detection is fundamental to a variety of database and analytic tasks. Recently, distance-based outlier detection has emerged as a viable and scalable alternative to traditional statistical and geometric approaches. In this article we explore the role of ranking for the efficient discovery of distance-based outliers from large high dimensional data sets. Specifically, we develop a light-weight...
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