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This paper presents a novel probability based approach for distinguishing between keyword and stopword from a text corpus. This has a lot of applications including automatic construction of stopword list. First objective of this paper is to investigate the role of probability distribution for distinguishing between
Automatically assigning relevant text keywords to images is an important problem. Many algorithms have been proposed in the past decade and achieved good performance. Efforts have focused upon model representations of keywords, but properties of features have not been well investigated. In most cases, a group of
Security attacks typically result from unintended behaviors or invalid inputs. Security testing is labor intensive because a real-world program usually has too many invalid inputs. It is highly desirable to automate or partially automate security-testing process. This paper presents an approach to automated generation of security tests by using formal threat models represented as Predicate/Transition...
traceability. Traceability will trace the keywords in the requirement to be converted into UML Diagram as proposed. This paper present review on available approaches and tools to support the transformation of requirement into behavior model. The main objective of this paper is to describe and presents the review of the benefits
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