Interpretation of Short Text Using Semantic Knowledge

Interpretation of short texts play a very vital role to many applications, but there are many challenges that come during their interpretation. First, short text is very frequently used in day-to-day life, which increases the ambiguity, and make the text-understanding complex making them difficult to handle. Second, the conventional and regular natural language tools cannot be implied on the text easily as short text do not always monitor the structure of the text. Third, discovery of hidden semantic structure in text body cannot be applicable on short text, as they do not hold sufficient statistical signals. Semantic search and information retrieval are the integral part of the search engine. We required a semantic knowledge for their understanding. In this work, we build a system, which uses the semantic analysis methodologies like part-of-speech tagging, text segmentation and concept labelling along with KNN algorithm. We applied KNN algorithm on a well-known knowledge base, which gives the semantic knowledge on the better interpretation on short text.