Open AccessA Statistical Model for GIST Generation : A Case Study on Hindi News Article
Author(s) -
Varaprasad Rao M,
Vishnu Vardhan B,
Vijay Pal Reddy P
Publication year - 2013
Publication title -
international journal of data mining and knowledge management process
Language(s) - English
Resource type - Journals
eISSN - 2231-007X
pISSN - 2230-9608
DOI - 10.5121/ijdkp.2013.3502
Subject(s) - hindi , computer science , gist , natural language processing , artificial intelligence , information retrieval , medicine , stromal cell , pathology
Every day, huge number of news articles are reported and disseminated on the Internet. By generating gistof an article, reader can go through the main topics instead of reading the whole article as it takes muchtime for reader to read the entire content of the article. An ideal system would understand the document and generate the appropriate theme(s) directly from the results of the understanding. In the absence of natural language understanding system, it is required to design an appropriate system. Gist generation is a difficult task because it requires both maximizing text content in short summary and maintains grammaticality of the text. In this paper we present a statistical approach to generate a gist of a Hindi news article. The experimental results are evaluated using the standard measures such as precision, recall and F1 measure for different statistical models and their combination on the article before pre-processing and after pre-processin