The Experts below are selected from a list of 53994 Experts worldwide ranked by ideXlab platform

Jianshe Dong - One of the best experts on this subject based on the ideXlab platform.

  • ISNN (2) - Research of Spam Filtering System Based on LSA and SHA
    Lecture Notes in Computer Science, 1
    Co-Authors: Jingtao Sun, Qiuyu Zhang, Zhanting Yuan, Wenhan Huang, Xiaowen Yan, Jianshe Dong
    Abstract:

    Along with the widespread concern of spam problem, at present, there are spam filtering system nowadays about the problem of semantic imperfection and spam filter low effect in the multi-send spam. This paper proposes a model of spam filtering which based on latent semantic analysis (LSA) and message-digest algorithm 5 (SHA). Making use of the LSA marks the latent feature phrase in the spam, semantic analysis is led into the spam filtering technique; the "e-mail fingerprint" of multi-send spam is born with SHA on the LSA analytical foundation, the problem of filtering technique's low effect in the multi-send spam is resolved with this kind of method. We have designed a spam filtering system based on this model. Our designed system was evaluated with an optional dataset. The results obtained were compared with KNN algorithm filter experiment results show that system based on Latent Semantic Analysis and SHA performs KNN. The experiments show the expected results obtained, and the feasibility and advantage of the new spam filtering method is validated.

Sartid Vongpradhip - One of the best experts on this subject based on the ideXlab platform.

  • A Technique to Add Error Detection of QR Code Decoding by Using Micro QR Code
    International Journal of Electrical Energy, 2013
    Co-Authors: Tanee Wiputtikul, Sartid Vongpradhip
    Abstract:

    This paper introduced method for error detection of the information in QR Code by using Micro QR Code, by creating a grayscale QR Code. Image processing technique is used before decoding. Image processing offer ability of fixing error and restore module that have been damage such as tear, stain or bend before decoding process. General QR Code has no error detection which helps to verify the correctness of information in QR Code. Therefore, the contents of Micro QR Code is generated using MD5 (message-digest algorithm 5) and overlapping onto the three corners of Finder Pattern of standard QR Code. The experiment is conducted on QR Code version 5 and over. The decoding is done by focusing on the region of interest on the overlapped Micro QR Code. After that the binarization is done using multilevel-threshoding to separate the content of the Micro QR Code. The opening technique is used to remove edges, eliminate noises and compare the decoding data. 

Jingtao Sun - One of the best experts on this subject based on the ideXlab platform.

  • Application of Refined LSA and MD5 algorithms in Spam Filtering
    Journal of Computers, 2009
    Co-Authors: Jingtao Sun, Qiuyu Zhang, Zhanting Yuan
    Abstract:

    The paper proposes a spam filtering method that uses integrated and refined Latent Semantic Analysis (LSA) and message-digest algorithm 5 (MD5) algorithms to address a series of universal problems in spam filtering, including remarkably lowered filtering precision and notably unbalanced filtering efficiency as a result of lack of latent semantic analysis of mail contents. In introducing LSA, its weighting function is improved by integrating fuzzy membership to improve effectiveness of LSA in processing mail contents. On top of this, MD5 algorithm is used to generate “E-mail fingerprint”, thus enabling quick matching and realizing highly efficient and accurate processing of mass- mailing spam. The result of the simulation experiment testifies effectiveness of the method.

  • ISNN (2) - Research of Spam Filtering System Based on LSA and SHA
    Lecture Notes in Computer Science, 1
    Co-Authors: Jingtao Sun, Qiuyu Zhang, Zhanting Yuan, Wenhan Huang, Xiaowen Yan, Jianshe Dong
    Abstract:

    Along with the widespread concern of spam problem, at present, there are spam filtering system nowadays about the problem of semantic imperfection and spam filter low effect in the multi-send spam. This paper proposes a model of spam filtering which based on latent semantic analysis (LSA) and message-digest algorithm 5 (SHA). Making use of the LSA marks the latent feature phrase in the spam, semantic analysis is led into the spam filtering technique; the "e-mail fingerprint" of multi-send spam is born with SHA on the LSA analytical foundation, the problem of filtering technique's low effect in the multi-send spam is resolved with this kind of method. We have designed a spam filtering system based on this model. Our designed system was evaluated with an optional dataset. The results obtained were compared with KNN algorithm filter experiment results show that system based on Latent Semantic Analysis and SHA performs KNN. The experiments show the expected results obtained, and the feasibility and advantage of the new spam filtering method is validated.

Zhanting Yuan - One of the best experts on this subject based on the ideXlab platform.

  • Application of Refined LSA and MD5 algorithms in Spam Filtering
    Journal of Computers, 2009
    Co-Authors: Jingtao Sun, Qiuyu Zhang, Zhanting Yuan
    Abstract:

    The paper proposes a spam filtering method that uses integrated and refined Latent Semantic Analysis (LSA) and message-digest algorithm 5 (MD5) algorithms to address a series of universal problems in spam filtering, including remarkably lowered filtering precision and notably unbalanced filtering efficiency as a result of lack of latent semantic analysis of mail contents. In introducing LSA, its weighting function is improved by integrating fuzzy membership to improve effectiveness of LSA in processing mail contents. On top of this, MD5 algorithm is used to generate “E-mail fingerprint”, thus enabling quick matching and realizing highly efficient and accurate processing of mass- mailing spam. The result of the simulation experiment testifies effectiveness of the method.

  • ISNN (2) - Research of Spam Filtering System Based on LSA and SHA
    Lecture Notes in Computer Science, 1
    Co-Authors: Jingtao Sun, Qiuyu Zhang, Zhanting Yuan, Wenhan Huang, Xiaowen Yan, Jianshe Dong
    Abstract:

    Along with the widespread concern of spam problem, at present, there are spam filtering system nowadays about the problem of semantic imperfection and spam filter low effect in the multi-send spam. This paper proposes a model of spam filtering which based on latent semantic analysis (LSA) and message-digest algorithm 5 (SHA). Making use of the LSA marks the latent feature phrase in the spam, semantic analysis is led into the spam filtering technique; the "e-mail fingerprint" of multi-send spam is born with SHA on the LSA analytical foundation, the problem of filtering technique's low effect in the multi-send spam is resolved with this kind of method. We have designed a spam filtering system based on this model. Our designed system was evaluated with an optional dataset. The results obtained were compared with KNN algorithm filter experiment results show that system based on Latent Semantic Analysis and SHA performs KNN. The experiments show the expected results obtained, and the feasibility and advantage of the new spam filtering method is validated.

Qiuyu Zhang - One of the best experts on this subject based on the ideXlab platform.

  • Application of Refined LSA and MD5 algorithms in Spam Filtering
    Journal of Computers, 2009
    Co-Authors: Jingtao Sun, Qiuyu Zhang, Zhanting Yuan
    Abstract:

    The paper proposes a spam filtering method that uses integrated and refined Latent Semantic Analysis (LSA) and message-digest algorithm 5 (MD5) algorithms to address a series of universal problems in spam filtering, including remarkably lowered filtering precision and notably unbalanced filtering efficiency as a result of lack of latent semantic analysis of mail contents. In introducing LSA, its weighting function is improved by integrating fuzzy membership to improve effectiveness of LSA in processing mail contents. On top of this, MD5 algorithm is used to generate “E-mail fingerprint”, thus enabling quick matching and realizing highly efficient and accurate processing of mass- mailing spam. The result of the simulation experiment testifies effectiveness of the method.

  • ISNN (2) - Research of Spam Filtering System Based on LSA and SHA
    Lecture Notes in Computer Science, 1
    Co-Authors: Jingtao Sun, Qiuyu Zhang, Zhanting Yuan, Wenhan Huang, Xiaowen Yan, Jianshe Dong
    Abstract:

    Along with the widespread concern of spam problem, at present, there are spam filtering system nowadays about the problem of semantic imperfection and spam filter low effect in the multi-send spam. This paper proposes a model of spam filtering which based on latent semantic analysis (LSA) and message-digest algorithm 5 (SHA). Making use of the LSA marks the latent feature phrase in the spam, semantic analysis is led into the spam filtering technique; the "e-mail fingerprint" of multi-send spam is born with SHA on the LSA analytical foundation, the problem of filtering technique's low effect in the multi-send spam is resolved with this kind of method. We have designed a spam filtering system based on this model. Our designed system was evaluated with an optional dataset. The results obtained were compared with KNN algorithm filter experiment results show that system based on Latent Semantic Analysis and SHA performs KNN. The experiments show the expected results obtained, and the feasibility and advantage of the new spam filtering method is validated.