Difference between revisions of "MC"
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| − | + | {{Entry | |
| + | |Name=MC | ||
| + | |Short description=Converts text documents into a vector space model. | ||
| + | |Full description=MC is a C++ program that creates vector-space models from text documents that can be used for text mining applications. MC provides an efficient multi-threaded implementation that can process very large document collections. The MC program: 1. Recursively descends directories, finding text files 2. Processes files selectively through full regular expression matching of file names. 3. Builds a sparse matrix of word/token counts. The particular sprse marix format used is given here. 4. Processes any user specified text formats(email address or URLs) as a whole token through regular expression matching or FLEX definition. 5. Prunes vocabulary by word length and frequency 6. Excludes user specified stop words 7. Sets word vector weights according any of the txx, txn, tfn, tfx, lxx, lxn, lfn, lfx scaling schemes. 8. Writes all data structures to disk in the Compressed Column Storage format. The application does not have English parsing or part-of-speech tagging facilities or complete documentation | ||
| + | |Homepage URL=https://web.archive.org/web/20090921192233/http://www.cs.utexas.edu/users/jfan/dm/ | ||
| + | |Is High Priority Project=No | ||
| + | |Decommissioned or Obsolete=No | ||
| + | |Keywords=data-mining,text-mining,vector-space-model,bag-of-words | ||
| + | |Version identifier=2.29 | ||
| + | |Version date=2004/11/09 | ||
| + | |Version status=stable | ||
| + | |Version download=https://web.archive.org/web/20090723195805/http://www.cs.utexas.edu/users/jfan/dm/src/mc.src.2.29.tar.gz | ||
| + | |Last review by=Bendikker | ||
| + | |Last review date=2017/02/20 | ||
| + | |Submitted by=Database conversion | ||
| + | |Submitted date=2011-04-01 | ||
| + | |User level=none | ||
| + | |Accepts cryptocurrency donations=No | ||
| + | |Test entry=No | ||
| + | |Is GNU=No | ||
| + | |License verified date=2001-07-02 | ||
| + | }} | ||
| + | {{Project license | ||
| + | |License=GPLv2orlater | ||
| + | |License verified by=Bendikker | ||
| + | |License verified date=2019/01/17 | ||
| + | }} | ||
| + | {{Person | ||
| + | |Real name=James Fan | ||
| + | |Role=Maintainer | ||
| + | |Email=jfan@cs.utexas.edu | ||
| + | }} | ||
| + | {{Software category | ||
| + | |Database=administration | ||
| + | |Interface=command-line | ||
| + | |Programming-language=C, C++ | ||
| + | |Runs-on=GNU/Linux | ||
| + | |Works-with=database | ||
| + | }} | ||
| + | {{Software prerequisite | ||
| + | |Prerequisite kind=Required to build | ||
| + | |Prerequisite description=[[STL]] | ||
| + | }} | ||
| + | {{Software prerequisite | ||
| + | |Prerequisite kind=Required to build | ||
| + | |Prerequisite description=[[pthread]] library | ||
| + | }} | ||
| + | {{Software prerequisite | ||
| + | |Prerequisite kind=Required to build | ||
| + | |Prerequisite description=[[FLEX]] | ||
| + | }} | ||
| + | {{Featured}} | ||
Latest revision as of 18:36, 17 January 2019
MC
https://web.archive.org/web/20090921192233/http://www.cs.utexas.edu/users/jfan/dm/
Converts text documents into a vector space model.
MC is a C++ program that creates vector-space models from text documents that can be used for text mining applications. MC provides an efficient multi-threaded implementation that can process very large document collections. The MC program: 1. Recursively descends directories, finding text files 2. Processes files selectively through full regular expression matching of file names. 3. Builds a sparse matrix of word/token counts. The particular sprse marix format used is given here. 4. Processes any user specified text formats(email address or URLs) as a whole token through regular expression matching or FLEX definition. 5. Prunes vocabulary by word length and frequency 6. Excludes user specified stop words 7. Sets word vector weights according any of the txx, txn, tfn, tfx, lxx, lxn, lfn, lfx scaling schemes. 8. Writes all data structures to disk in the Compressed Column Storage format. The application does not have English parsing or part-of-speech tagging facilities or complete documentation
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