The Experts below are selected from a list of 45990 Experts worldwide ranked by ideXlab platform
Ardalan Amiri Sani - One of the best experts on this subject based on the ideXlab platform.
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MobiSys - SchrodinText: Strong Protection of Sensitive Textual Content of Mobile Applications
Proceedings of the 15th Annual International Conference on Mobile Systems Applications and Services, 2017Co-Authors: Ardalan Amiri SaniAbstract:Many mobile applications deliver and show sensitive and private Textual Content to users including messages, social network posts, account information, and verification codes. All such Textual Content must only be displayed to the user but must be strongly protected from unauthorized access in the device. Unfortunately, this is not the case in mobile devices today: malware that can compromise the operating system, e.g., gain root or kernel privileges, can easily access Textual Content of other applications. In this paper, we present SchrodinText, a system solution for strongly protecting the confidentiality of application's selected UI Textual Content from a fully compromised operating system. SchrodinText leverages a novel security monitor based on two hardware features on modern ARM processors: virtualization hardware and TrustZone. Our key contribution is a set of novel techniques that allow the operating system to perform the text rendering without needing access to the text itself, hence minimizing the Trusted Computing Base (TCB). These techniques, collectively called oblivious rendering, enable the operating system to rasterize and lay out all the characters without access to the text; the monitor only resolves the right character glyphs onto the framebuffer observed by the user and protects them from the operating system, e.g., against DMA attacks. We present our prototype using an ARM Juno development board and Android operating system. We show that SchrodinText incurs noticeable overhead but that its performance is usable.
Pierre-françois Marteau - One of the best experts on this subject based on the ideXlab platform.
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SIRIUS XML IR System at INEX 2006: Approximate Matching of Structure and Textual Content
2006Co-Authors: Eugen Popovici, Gildas Ménier, Pierre-françois MarteauAbstract:In this paper we report on the retrieval approach taken by the VALORIA laboratory of the University of South-Brittany while participating at INEX 2006 ad-hoc track with the SIRIUS XML IR system. SIRIUS retrieves relevant XML elements by approximate matching both the Content and the structure of the XML documents. A weighted editing distance on XML paths is used to approximately match the documents structure while the IDF of the researched terms are used to rank the Textual Content of the retrieved elements. We briefly describe the approach and the extensions made to the SIRIUS XML IR system to address each of the four subtasks of the INEX 2006 ad-hoc track. Finally we present and analyze the SIRIUS retrieval evaluation results. SIRIUS runs were ranked on the 1st position out of 77 submitted runs for the Best In Context task and obtained several top ten results for both the Focused and All In Context tasks.
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INEX - SIRIUS XML IR System at INEX 2006: Approximate Matching of Structure and Textual Content
Comparative Evaluation of XML Information Retrieval Systems, 1Co-Authors: Eugen Popovici, Gildas Ménier, Pierre-françois MarteauAbstract:In this paper we report on the retrieval approach taken by the VALORIA laboratory of the University of South-Brittany while participating at INEX 2006 ad-hoc track with the SIRIUS XML IR system. SIRIUS retrieves relevant XML elements by approximate matching both the Content and the structure of the XML documents. A weighted editing distance on XML paths is used to approximately match the documents structure while the IDF of the researched terms are used to rank the Textual Content of the retrieved elements. We briefly describe the approach and the extensions made to the SIRIUS XML IR system to address each of the four subtasks of the INEX 2006 ad-hoc track. Finally we present and analyze the SIRIUS retrieval evaluation results. SIRIUS runs were ranked on the 1st position out of 77 submitted runs for the Best In Context task and obtained several top ten results for both the Focused and All In Context tasks.
Yonghua Zhu - One of the best experts on this subject based on the ideXlab platform.
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Transfer Correlation Between Textual Content to Images for Sentiment Analysis
IEEE Access, 2020Co-Authors: Ke Zhang, Yunwen Zhu, Wenjun Zhang, Weilin Zhang, Yonghua ZhuAbstract:In social media, images and texts are used to convey individuals’ attitudes and feelings; thus, social media has become an indispensable part of people’s lives. To understand social behavior and provide better recommendations, sentiment analysis on social media is helpful. One sentiment analysis task is polarity prediction. Although current research on visual or Textual sentiment analysis has achieved quite good progress, multimodal and cross-modal analysis combining visual and Textual correlation is still in the exploration stage. To capture a semantic connection between images and captions, this paper proposes a cross-modal approach that considers both images and captions in classifying image sentiment polarity. This method transfers the correlation between Textual Content to images. First, the image and its corresponding caption are sent into an inner-class mapping model, where they are transformed into vectors in Hilbert space to obtain their labels by calculating the inner-class maximum mean discrepancy (MMD). Then, a class-aware sentence representation (CASR) model assigns the distributed representation to the labels with a class-aware attention-based gated recurrent unit (GRU). Finally, an inner-class dependency LSTM (IDLSTM) classifies the sentiment polarity. Experiments carried out on the Getty Images dataset and Twitter 1269 dataset demonstrate the effectiveness of our approach. Moreover, extensive experimental results show that our model outperforms baseline solutions.
Ali Khenchaf - One of the best experts on this subject based on the ideXlab platform.
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Visual and Textual Content based indexing and retrieval
International Journal on Digital Libraries, 2000Co-Authors: Chaabane Djeraba, Marinette Bouet, Henri Briand, Ali KhenchafAbstract:Although there are several research and commercial systems in Content-based multimedia indexing and retrieval, more effort should be focused on the quality of retrieval, particularly regarding how well the retrieval results correspond to what the user really wants. In this context, we present an approach that may contribute to the quality of indexing and retrieval. It supports both Textual and visual indexing and retrieval that obtains results with a higher degree of quality, and it incorporates domain knowledge into the index without any special efforts on the part of the user.
Eugen Popovici - One of the best experts on this subject based on the ideXlab platform.
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SIRIUS XML IR System at INEX 2006: Approximate Matching of Structure and Textual Content
2006Co-Authors: Eugen Popovici, Gildas Ménier, Pierre-françois MarteauAbstract:In this paper we report on the retrieval approach taken by the VALORIA laboratory of the University of South-Brittany while participating at INEX 2006 ad-hoc track with the SIRIUS XML IR system. SIRIUS retrieves relevant XML elements by approximate matching both the Content and the structure of the XML documents. A weighted editing distance on XML paths is used to approximately match the documents structure while the IDF of the researched terms are used to rank the Textual Content of the retrieved elements. We briefly describe the approach and the extensions made to the SIRIUS XML IR system to address each of the four subtasks of the INEX 2006 ad-hoc track. Finally we present and analyze the SIRIUS retrieval evaluation results. SIRIUS runs were ranked on the 1st position out of 77 submitted runs for the Best In Context task and obtained several top ten results for both the Focused and All In Context tasks.
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INEX - SIRIUS XML IR System at INEX 2006: Approximate Matching of Structure and Textual Content
Comparative Evaluation of XML Information Retrieval Systems, 1Co-Authors: Eugen Popovici, Gildas Ménier, Pierre-françois MarteauAbstract:In this paper we report on the retrieval approach taken by the VALORIA laboratory of the University of South-Brittany while participating at INEX 2006 ad-hoc track with the SIRIUS XML IR system. SIRIUS retrieves relevant XML elements by approximate matching both the Content and the structure of the XML documents. A weighted editing distance on XML paths is used to approximately match the documents structure while the IDF of the researched terms are used to rank the Textual Content of the retrieved elements. We briefly describe the approach and the extensions made to the SIRIUS XML IR system to address each of the four subtasks of the INEX 2006 ad-hoc track. Finally we present and analyze the SIRIUS retrieval evaluation results. SIRIUS runs were ranked on the 1st position out of 77 submitted runs for the Best In Context task and obtained several top ten results for both the Focused and All In Context tasks.
