EMAS Framework For Text Plagarism Detection (Evolutionary Multi-Agent System)

摘要

Research ultimate goal remains to Enhance Science and Technology. Scientists, Research scholars and teacher are dedicated to research. But It has been Observed that in other to achieve success research methodology is been plagiarized. Investigating and Identifying Genuine Research innovation is demand of Todays research domain. Idea Innovation and Invention are vital for today's research domain. In context to Computer Technology algorithmic procedures, architecture Design are been commonly plagiarized without proper citation and referencing. Text Plagiarism is preliminary stage to evaluate any research work. Research Analysis Question Observed in Text Plagiarism is large unknown patterns and ever increasing unstructured data. Patterns change interestingly from research domains and no precise technique exists to retrieve them. Existing plagiarism detection system lack to sense information and merely work on keyword sense. Further Architecture of existing plagiarism detection system in not scalable. A decision Support System is been required which would learn over time as data grows in volume. Proposed research is implementation of Multi-agent system (MAS) with evolutionary Feature. Multi-Agent system assists in decision making and interestingly detect new Patterns of plagiarism adopted by scholars.