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Personalized And Adaptive Semantic Information Filtering For Social Media, Pavan Kapanipathi
Personalized And Adaptive Semantic Information Filtering For Social Media, Pavan Kapanipathi
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Social media has experienced immense growth in recent times. These platforms are becoming increasingly common for information seeking and consumption, and as part of its growing popularity, information overload pose a significant challenge to users. For instance, Twitter alone generates around 500 million tweets per day and it is impractical for users to have to parse through such an enormous stream to find information that are interesting to them. This situation necessitates efficient personalized filtering mechanisms for users to consume relevant, interesting information from social media. Building a personalized filtering system involves understanding users' interests and utilizing these interests to …
Framework For Semantic Integration And Scalable Processing Of City Traffic Events, Surendra Brahma Marupudi
Framework For Semantic Integration And Scalable Processing Of City Traffic Events, Surendra Brahma Marupudi
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Intelligent traffic management requires analysis of a large volume of multimodal data from diverse domains. For the development of intelligent traffic applications, we need to address diversity in observations from physical sensors which give weather, traffic flow, parking information; we also need to do the same with social media, which provides live commentary of various events in a city. The extraction of relevant events and the semantic integration of numeric values from sensors, unstructured text from Twitter, and semi- structured data from city authorities is a challenging physical-cyber-social data integration problem. In order to address the challenge of both scalability …
De-Anonymization Attack Anatomy And Analysis Of Ohio Nursing Workforce Data Anonymization, Jacob M. Miracle
De-Anonymization Attack Anatomy And Analysis Of Ohio Nursing Workforce Data Anonymization, Jacob M. Miracle
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Data generalization (anonymization) is a widely misunderstood technique for preserving individual privacy in non-interactive data publishing. Easily avoidable anonymization failures are still occurring 14 years after the discovery of basic techniques to protect against them. Identities of individuals in anonymized datasets are at risk of being disclosed by cyber attackers who exploit these failures. To demonstrate the importance of proper data anonymization we present three perspectives on data anonymization. First, we examine several de-anonymization attacks to formalize the anatomy used to conduct attacks on anonymous data. Second, we examine the vulnerabilities of an anonymous nursing workforce survey to convey how …
Knowledge Driven Search Intent Mining, Ashutosh Jadhav
Knowledge Driven Search Intent Mining, Ashutosh Jadhav
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Understanding users' latent intents behind search queries is essential for satisfying a user's search needs. Search intent mining can help search engines to enhance its ranking of search results, enabling new search features like instant answers, personalization, search result diversification, and the recommendation of more relevant ads. Hence, there has been increasing attention on studying how to effectively mine search intents by analyzing search engine query logs. While state-of-the-art techniques can identify the domain of the queries (e.g. sports, movies, health), identifying domain-specific intent is still an open problem. Among all the topics available on the Internet, health is one …