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PCSF: Privacy-Preserving Content-Based Spam Filter
IEEE Transactions on Information Forensics and Security, 2023The purpose of privacy-preserving spam filtering is to inspect email while preserving the privacy of its detection rules and the email content. Although many solutions have emerged, they suffer from the following: 1) The privacy provided is insufficient as the email content or detection rules may be exposed to third parties; 2) Due to improper use of ...
Intae Kim +4 more
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Content Based Spam E-mail Filtering
2016 International Conference on Collaboration Technologies and Systems (CTS), 2016Currently, E-mail is one of the most important methods of communication. However, the increasing of spam e-mails causes traffic congestion, decreasing productivity, phishing, which has become a serious problem for our society. And the number of spam e-mail is increasing every year.
Pingchuan Liu, Teng-Sheng Moh
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Content-Based Image Filtering for Recommendation
2006Content-based filtering can reflect content information, and provide recommendations by comparing various feature based information regarding an item. However, this method suffers from the shortcomings of superficial content analysis, the special recommendation trend, and varying accuracy of predictions, which relies on the learning method. In order to
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Evaluating content-based filters for image and video retrieval
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval, 2004This paper investigates the level of metadata accuracy required for image filters to be valuable to users. Access to large digital image and video collections is hampered by ambiguous and incomplete metadata attributed to imagery. Though improvements are constantly made in the automatic derivation of semantic feature concepts such as indoor, outdoor ...
Michael G. Christel +2 more
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What Happened to Content-Based Information Filtering?
2009Personalisation can have a significant impact on the way information is disseminated on the web today. Information Filtering can be a significant ingredient towards a personalised web. Collaborative Filtering is already being applied successfully for generating personalised recommendations of music tracks, books, movies and more.
Nikolaos Nanas +2 more
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A Framework for Collaborative, Content-Based and Demographic Filtering
Artificial Intelligence Review, 1999We discuss learning a profile of user interests for recommending information sources such as Web pages or news articles. We describe the types of information available to determine whether to recommend a particular page to a particular user. This information includes the content of the page, the ratings of the user on other pages and the contents of ...
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Content-based network filtering of encrypted image data
2010 IEEE International Conference on Wireless Communications, Networking and Information Security, 2010The proliferation of multimedia encryption techniques allows securing various applications including tele-browsing and visio-conferencing. However, these techniques may also constitute useful tools for malicious users to transmit prohibited data without being detected by preventive and reactive security mechanisms.
Mohamed Hamdi, Noureddine Boudriga
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Selecting content-based features for collaborative filtering recommenders
Proceedings of the 7th ACM conference on Recommender systems, 2013We study the problem of scoring and selecting content-based features for a collaborative filtering (CF) recommender system. Content-based features play a central role in mitigating the ``cold start'' problem in commercial recommenders. They are also useful in other related tasks, such as recommendation explanation and visualization.
Royi Ronen +3 more
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Content-Based Collaborative Filtering for News Topic Recommendation
Proceedings of the AAAI Conference on Artificial Intelligence, 2015News recommendation has become a big attraction with which major Web search portals retain their users. Two effective approaches are Content-based Filtering and Collaborative Filtering, each serving a specific recommendation scenario.
Zhongqi Lu +4 more
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Filter Similarities in Content-Based Publish/Subscribe Systems
2002Matching notifications to subscriptions and routing notifications from producers to interested consumers are the main problems in large-scale publish/subscribe systems.Most previously proposed distributed notification services either use flooding or, if filtering is performed, they assume that each event broker has global knowledge about all active ...
Gero Mühl +2 more
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