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    Analyze Cybersecurity documents with texting mining and machine learning techniques.

    by Bojian Zhang 1519760042000

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      I accept the terms and conditions (see side bar). I understand all content I am submitting must be licensed under an open-source software or Creative Commons license as described in the Terms and Conditions:

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      Description

      We will focus on the following improvements:

      1.Tokenization

      Make the connection of the sentences with similar meanings.

      Make sure to keep the completeness of the meaning of the sentences.

      2.Extraction.

      Extract more meaningful contents from the documents.

      3.Classification.

      Enhance the match accuracy of categorizations with sentences.

      4.Multi-lingual support.

      Perform classification on non-English documents.

      Main Challenges:

      1.Building a proper dictionary.

      2.Analyzing different languages.

      Methodology and Tools:

      Python NLP:Textract, NLTK, Goslate, Scikit Learn, Spacy

      Co-authors to your solution

      Chien Min Wang, Yichao Li, Aidi Li, Xiansheng Zhang

      Link to your concept design and documentation (Required by the final day of the Submission & Collaboration phase)

      https://github.com/UniteIdeas/CyberSecurityNLP/issues/1

      Link to an online working solution or prototype (Required by the final day of the Submission & Collaboration phase):

      https://github.com/UniteIdeas/CyberSecurityNLP/issues/1

      Link to a video or screencast of your solution or prototype (Required by the final day of the Submission & Collaboration phase):

      https://youtu.be/5KFF_vA7gJI

      Link to source code of your solution or prototype above. (If you submitted a link to an online solution or prototype, or to a video of your solution of prototype, you must provide a link to the source code. This item is required by the final day of the submission phase):

      https://github.com/UniteIdeas/CyberSecurityNLP/issues/1

      Total Reviews: 2
      Judge review
      Reviewed by: All Users
      Score: 75.0
      0 20 40 60 80 100
      Alignment with Challenge Objectives The idea is aligned with the strategic direction of the challenge. 1 = Strongly Disagree ; 5 = Strongly Agree

      Score: 80.0 Weight: 100

      Sound data analysis & accuracy of results The idea provides sound data analysis & accuracy of results. 1 = Strongly Disagree ; 5 = Strongly Agree

      Score: 80.0 Weight: 100

      Originality The idea adds originality that the market will value and/or is clearly an improvement over our/the current approach. 1 = Strongly Disagree ; 5 = Strongly Agree

      Score: 80.0 Weight: 100

      User FriendlinessThe idea is logical, useful, systematic, understandable, "do-able," not overly difficult or complex for the intended benefits. 1 = Strongly Disagree ; 5 = Strongly Agree

      Score: 60.0 Weight: 100

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      User Tasks ?
      Required for graduation.
      Task Assigned to Due Date Status
      Spigit Prototype
      Crowd Analytics
      Community and Analytical Tasks
      Community and Analytical Tasks Added Progress Status
      Spigit Prototype
      Contact your application administrator.

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