期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2018
卷号：7
期号：6
页码：7006-7013
DOI：10.15680/IJIRSET.2018.0706018
出版社：S&S Publications
摘要：Understanding short text is a crucial task, as the text are more ambiguous it is difficult to understand.
Short text are usually produced by search queries, tweets, conversation and tags. Short text are ambiguous and noisy as
the text has more than one meaning ,the text does not contain sufficient data it is difficult to handle. In the proposed
work we construct a model framework for seeing short content which misuses semantic information conveyed by a
notable knowledge base and this can be consequently reaped from a web corpus Our knowledge-intensive
methodologies disturb old-style methods for tasks such as part-of-speech tagging, text segmentation and the concept
labelling, in the sense that in all these tasks revolve around the semantics. On real-data a comprehensive performance
evaluation is being conducted here, the results for this show that to understand the short text semantic knowledge is
indispensable. The approaches we are using are both efficient and effective in identifying or discovering the semantics
of short texts.
