Improve Automatic Sentence Boundary Detection Through Support Vector Machine And Reduce Complexity
1Tarun Dhar Diwan, 2 Sunil Tiwari and 3 Bhoopendra dhar diwan
1 Researcher, Bilaspur (C.G), INDI Email. email@example.com 2Statistical Department, C. G. Govt., INDIA. 3 MPBOU, Bhopal (M.P), INDIA.
Soft Computing and Information Communication Technology (ICT) both are main part in information technology and computer science because today all documentations are computerized to store necessary information and database into English language, so natural language processing concept is come from A.I branch of computer science and information technology as part of soft computing and ICT(information communication technology). Here English language may be used as a major part of machine learning method ,where sentence boundary detection is a great challenge in current time of nlp(natural language processing).So SVM(support vector machine) can be used to solve the problem of sentence boundary detection which indicates the machine learning method regarding efficient soft computing and ICT. Hence Computer system may be learned to avoid ambiguity of dot(.) periods in detecting sentence boundary.
Keyword:- SVM(support vector machine), true positives, false positives, true negatives, false negatives, precision, recall, f feature, SBD(sentence boundary detection).
International eJournal of Mathematical Sciences, Technology and Humanities
Volume 2, Issue 1, Pages: 243 - 248