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普渡大学UNIX命令历史记录数据集

普渡大学UNIX命令历史记录数据集

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Terran Lane:terran '@' ecn.purdue.eduData Set Information:This file contains 9 sets of sanitized user data drawn......

数据结构 ? 161K

    Data Structure ?

    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md

    Terran Lane:
    terran '@' ecn.purdue.edu


    Data Set Information:

    This file contains 9 sets of sanitized user data drawn from the
    command histories of 8 UNIX computer users at Purdue over the course
    of up to 2 years (USER0 and USER1 were generated by the same person,
    working on different platforms and different projects).  The data is
    drawn from tcsh(1) history files and has been parsed and sanitized to
    remove filenames, user names, directory structures, web addresses,
    host names, and other possibly identifying items.  Command names,
    flags, and shell metacharacters have been preserved.  Additionally,
    **SOF** and **EOF** tokens have been inserted at the start and end of
    shell sessions, respectively.  Sessions are concatenated by date order
    and tokens appear in the order issued within the shell session, but no
    timestamps are included in this data.  For example, the two sessions:

    	# Start session 1
    	cd ~/private/docs
    	ls -laF | more
    	cat foo.txt bar.txt zorch.txt > somewhere
    	exit
    	# End session 1
    
    	# Start session 2
    	cd ~/games/
    	xquake &
    	fg
    	vi scores.txt
    	mailx 
    	exit
    	# End session 2


    would be represented by the token stream

    	**SOF**
    	cd



    Attribute Information:

    N/A


    Relevant Papers:

    N/A


    Papers That Cite This Data Set1:

    Stefan Aeberhard and Danny Coomans and De Vel. THE PERFORMANCE OF STATISTICAL PATTERN RECOGNITION METHODS IN HIGH DIMENSIonAL SETTINGS. James Cook University.  [View Context].


    Citation Request:

    This data is made available under conditions of anonymity for the contributing users and may be used for research purposes only. Summaries and research results employing this data may be published, but literal tokens or token sequences from the data may not be published except with express consent of the originators of the data. No portion of this data may be released with or included in a commercial product, nor may any portion of this data be sold or redistributed for profit or as part of of a profit-making endeavor.

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