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Understanding Short Text Through Lexical Semantic Analysis
Author(s) -
J. Shobana,
S. Amutha,
M. Murali
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1130/1/012038
Subject(s) - computer science , natural language processing , parsing , artificial intelligence , natural language understanding , syntax , knowledge base , segmentation , semantics (computer science) , gadget , natural language , information retrieval , programming language , algorithm
Information of quick texts is crucial for many packages however there are many demanding situations. First, the fast texts do not constantly look at a written language’s syntax. As a end result, traditional natural language processing gear cannot be without problems applied, ranging from element-of-talk tagging to dependency parsing. second, brief texts usually do now not incorporate sufficient statistical signals to help a few of the state of play Thirdly, short texts are greater ambiguous land noisier, land are generated in a big quantity, which further will increase the problem of coping with them. We argue that semantic knowledge is important for better understanding of brief texts. on this paintings, we build a prototype gadget for short text expertise that takes advantage of semantic expertise furnished by using a famous know-how base and harvests it automatically Our methods for responsibilities which includes text segmentation, component-of-speech tagging, and idea labeling, inside the feel that during these kind of duties we awareness on semantic. We perform a complete evaluation of the overall performance on actual-existence facts. The outcomes display that semantic information is critical for the understanding of quick texts and our information-intensive technique.

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