News feed is one of the potential information providing sources which give updates on various topics of different domains.These updates on various topics need to be collected since the domain specific interested users...News feed is one of the potential information providing sources which give updates on various topics of different domains.These updates on various topics need to be collected since the domain specific interested users are in need of important updates in their domains with organized data from various sources.In this paper,the news summarization system is proposed for the news data streams from RSS feeds and Google news.Since news stream analysis requires live content,the news data are continuously collected for our experimentation.Themajor contributions of thiswork involve domain corpus based news collection,news content extraction,hierarchical clustering of the news and summarization of news.Many of the existing news summarization systems lack in providing dynamic content with domain wise representation.This is alleviated in our proposed systemby tagging the news feed with domain corpuses and organizing the news streams with the hierarchical structure with topic wise representation.Further,the news streams are summarized for the users with a novel summarization algorithm.The proposed summarization system generates topic wise summaries effectively for the user and no system in the literature has handled the news summarization by collecting the data dynamically and organizing the content hierarchically.The proposed system is compared with existing systems and achieves better results in generating news summaries.The Online news content editors are highly benefitted by this system for instantly getting the news summaries of their domain interest.展开更多
Preserving privacy of the user is a very critical requirement to be metwith all the international laws like GDPR, California privacy protection act andmany other bills in place. On the other hand, Online Social Networ...Preserving privacy of the user is a very critical requirement to be metwith all the international laws like GDPR, California privacy protection act andmany other bills in place. On the other hand, Online Social Networks (OSN)has a wide spread recognition among the users, as a means of virtual communication. OSN may also acts as an identity provider for both internal and externalapplications. While it provides a simplified identification and authentication function to users across multiple applications, it also opens the users to a new spectrum of privacy threats. The privacy breaches costs to the users as well as tothe OSN. Despite paying millions of dollars as fine every year, the OSN hasnot done any significant changes, as data is the fuel and what it loses as fine isfar less compared to the money OSN makes out of the shared data. In this work,we have discussed a wide range of possible privacy threats and solutions prevailing in OSN-Third Party Application (TPA) data sharing scenario. Our solutionmodels the behavior of the user, as well as TPA and pinpoints the avenues of oversharing to the users, thereby limiting the privacy loss of the user.展开更多
文摘News feed is one of the potential information providing sources which give updates on various topics of different domains.These updates on various topics need to be collected since the domain specific interested users are in need of important updates in their domains with organized data from various sources.In this paper,the news summarization system is proposed for the news data streams from RSS feeds and Google news.Since news stream analysis requires live content,the news data are continuously collected for our experimentation.Themajor contributions of thiswork involve domain corpus based news collection,news content extraction,hierarchical clustering of the news and summarization of news.Many of the existing news summarization systems lack in providing dynamic content with domain wise representation.This is alleviated in our proposed systemby tagging the news feed with domain corpuses and organizing the news streams with the hierarchical structure with topic wise representation.Further,the news streams are summarized for the users with a novel summarization algorithm.The proposed summarization system generates topic wise summaries effectively for the user and no system in the literature has handled the news summarization by collecting the data dynamically and organizing the content hierarchically.The proposed system is compared with existing systems and achieves better results in generating news summaries.The Online news content editors are highly benefitted by this system for instantly getting the news summaries of their domain interest.
文摘Preserving privacy of the user is a very critical requirement to be metwith all the international laws like GDPR, California privacy protection act andmany other bills in place. On the other hand, Online Social Networks (OSN)has a wide spread recognition among the users, as a means of virtual communication. OSN may also acts as an identity provider for both internal and externalapplications. While it provides a simplified identification and authentication function to users across multiple applications, it also opens the users to a new spectrum of privacy threats. The privacy breaches costs to the users as well as tothe OSN. Despite paying millions of dollars as fine every year, the OSN hasnot done any significant changes, as data is the fuel and what it loses as fine isfar less compared to the money OSN makes out of the shared data. In this work,we have discussed a wide range of possible privacy threats and solutions prevailing in OSN-Third Party Application (TPA) data sharing scenario. Our solutionmodels the behavior of the user, as well as TPA and pinpoints the avenues of oversharing to the users, thereby limiting the privacy loss of the user.
