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Document Summarization (ADS) systems are suitable for the task of outlining useful data. The ADS system model takes a text document as input, and outputs a semantically-relevant summary of this information. This information can be further separated and outlined as keywords, or keyphrases. This paper proposes a novel
The number of Web services are growing rapidly on the Internet. Topics of services are becoming various. Semantic-based keyword search is used to retrieve proper services for service consumers. According to the semantic information implied in service database, we build a topic model to cluster and management related
between cloud computing and big data by employing keyword co-occurrence analysis on scientific publications. Following that, this paper explores the case of Malaysia as cloud computing service sector has emerged and there is focus on adoption of big data. Subsequently, new opportunities for cloud service providers in
types of keywords with different linking roles are conducted to discover the possible distribution law. Experimental results show that these keywords with association role reveal previous power-law distribution. Then, based on the discovered power-law distribution, up-cutting and down-cutting points are presented to divide
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