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Term Space Partition Based Ensemble Feature Construction for Spam Detection

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Book cover Data Mining and Big Data (DMBD 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9714))

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Abstract

This paper proposes an ensemble feature construction method for spam detection by using the term space partition (TSP) approach, which aims to establish a mechanism to make terms play more sufficient and rational roles by dividing the original term space and constructing discriminative features on distinct subspaces. The ensemble features are constructed by taking both global and local features of emails into account in feature perspective, where variable-length sliding window technique is adopted. Experiments conducted on five benchmark corpora suggest that the ensemble feature construction method far outperforms not only the traditional and most widely used bag-of-words model, but also the heuristic and state-of-the-art immune concentration based feature construction approaches. Compared to the original TSP approach, the ensemble method achieves better performance and robustness, providing an alternative mechanism of reliability for different application scenarios.

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Acknowlegements

This work was supported by the Natural Science Foundation of China (NSFC) under grant no. 61375119 and the Beijing Natural Science Foundation under grant no. 4162029, and partially supported by National Key Basic Research Development Plan (973 Plan) Project of China under grant no. 2015CB352302.

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Authors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), Peking University, Beijing, 100871, China

    Guyue Mi, Yang Gao & Ying Tan

  2. Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, Beijing, 100871, China

    Guyue Mi, Yang Gao & Ying Tan

Authors
  1. Guyue Mi
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  2. Yang Gao
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  3. Ying Tan
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Corresponding author

Correspondence to Ying Tan .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Xi'an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

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Mi, G., Gao, Y., Tan, Y. (2016). Term Space Partition Based Ensemble Feature Construction for Spam Detection. In: Tan, Y., Shi, Y. (eds) Data Mining and Big Data. DMBD 2016. Lecture Notes in Computer Science(), vol 9714. Springer, Cham. https://doi.org/10.1007/978-3-319-40973-3_20

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  • DOI: https://doi.org/10.1007/978-3-319-40973-3_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40972-6

  • Online ISBN: 978-3-319-40973-3

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