%0 Journal Article %1 S__2015 %A Mane, Mr. G. S. %A Kulkarni, Mrs. A. R. %D 2015 %I Auricle Technologies, Pvt., Ltd. %J International Journal on Recent and Innovation Trends in Computing and Communication %K (NLP) (PRA) API Algorithm Disambiguation Entailment Language Natural Phrase Processing Reinforcement Sense Textual Twitter Word WordNet %N 2 %P 427--430 %R 10.17762/ijritcc2321-8169.150201 %T Twitter Event Summarization Using Phrase Reinforcement Algorithm and NLP Features %U http://dx.doi.org/10.17762/ijritcc2321-8169.150201 %V 3 %X Abstract-Now a day’s social networking sites are the fastest medium which delivers news to user as compare to the news paper and television. There so many social networking sites are present and one of them is Twitter. Twitter allows large no. of users to share/post their views, ideas on any particular event. According to recent survey daily 340 million Tweets are sent on Twitter which is on a different topic and only 4% of posts on Twitter have relevant news data. It is not possible for any human to read the posts to get meaningful information related to specific event. There is one solution to this problem i.e. we have to apply Summarization technique on it. In this paper we have used an algorithm which uses frequency count technique along with this we have also used some NLP features to summarize event specified by user. This automatic summarization algorithm handles the numerous, short, dissimilar, and noisy nature of tweets. We believe our novel approach helps users as well as researchers

@article{S__2015, abstract = {Abstract-Now a day’s social networking sites are the fastest medium which delivers news to user as compare to the news paper and television. There so many social networking sites are present and one of them is Twitter. Twitter allows large no. of users to share/post their views, ideas on any particular event. According to recent survey daily 340 million Tweets are sent on Twitter which is on a different topic and only 4% of posts on Twitter have relevant news data. It is not possible for any human to read the posts to get meaningful information related to specific event. There is one solution to this problem i.e. we have to apply Summarization technique on it. In this paper we have used an algorithm which uses frequency count technique along with this we have also used some NLP features to summarize event specified by user. This automatic summarization algorithm handles the numerous, short, dissimilar, and noisy nature of tweets. We believe our novel approach helps users as well as researchers}, added-at = {2015-08-04T06:20:57.000+0200}, author = {Mane, Mr. G. S. and Kulkarni, Mrs. A. R.}, biburl = {https://www.bibsonomy.org/bibtex/27546a1b3a89e9fc3c7267b23121c0585/ijritcc}, doi = {10.17762/ijritcc2321-8169.150201}, interhash = {c6d801736b74af15e9b818c54f1800b0}, intrahash = {7546a1b3a89e9fc3c7267b23121c0585}, journal = {International Journal on Recent and Innovation Trends in Computing and Communication}, keywords = {(NLP) (PRA) API Algorithm Disambiguation Entailment Language Natural Phrase Processing Reinforcement Sense Textual Twitter Word WordNet}, month = {february}, number = 2, pages = {427--430}, publisher = {Auricle Technologies, Pvt., Ltd.}, timestamp = {2015-08-04T06:20:57.000+0200}, title = {Twitter Event Summarization Using Phrase Reinforcement Algorithm and {NLP} Features}, url = {http://dx.doi.org/10.17762/ijritcc2321-8169.150201}, volume = 3, year = 2015 }