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software:rewinfomap [2010/12/05 19:23]
eapontep [Testing]
software:rewinfomap [2010/12/07 11:58] (current)
eapontep
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 The first step in order to build a model is to choose a directory where the models will be created. This is done by setting an environment variable <file bash>​INFOMAP_WORKING_DIR=/​home/​jrandom/​infomap_models The first step in order to build a model is to choose a directory where the models will be created. This is done by setting an environment variable <file bash>​INFOMAP_WORKING_DIR=/​home/​jrandom/​infomap_models
 export INFOMAP_WORKING_DIR</​file>​ export INFOMAP_WORKING_DIR</​file>​
- 
 Afterwards run build the model. Informap accepts two formats: a single file where documents are divided by xml markers or as set of files, where every file contains exactly one document. I decided to use this second option. As input, there should be a file specifying the name of file containing a document.<​file bash>​infomap-build -m /​usr/​local/​share/​corpora/​manyNames.txt many_01</​file>​ Afterwards run build the model. Informap accepts two formats: a single file where documents are divided by xml markers or as set of files, where every file contains exactly one document. I decided to use this second option. As input, there should be a file specifying the name of file containing a document.<​file bash>​infomap-build -m /​usr/​local/​share/​corpora/​manyNames.txt many_01</​file>​
 +Remember to add Infomap to your PATH variable. The installation includes a manual of all the applications available. ​
 +In corpora directory, you will find a simple py script for building a corpora from a file where every line is a document. Afterwards I used the following command:<​file bash>​infomap-build -m /​net/​data/​CL/​projects/​wordspace/​software_tests/​corpora/​infoCorpus/​directory.txt firstModel</​file>​
 +In order to change the default configuration of the model, you would need to change the file: ??. I ran tests only with the default configuration (including reduction to 100 dimension). '​directory.txt'​ is a file containing the name of every file-document in the directory where the corpus is saved. Although the manual doesn'​t specify what markers should be used, including every file-name in a new line works out. The option '​-m'​ (or '​-sf'​ for single file) specifies the type of corpus. Finally, '​fistModel'​ is the name of the model created in '​INFOMAP_WORKING_DIR'​.
 +Two tests were run and the resulting models are available in the server: firstModel (using approximately 30000 documents -minus corrupted documents- in the Wiki Corpus. Constructing the model took me less than five minutes and the resulting directory occupies 65Mb. 
 +
 +{{:​software:​vizinfo1.png|}}
  
-Remember to add infomap to your PATH variable.+A second test was conducted again with the Wiki-Corpus,​ this time with 200000 documentsConstructing the model take less than 10 minutes. The resulting directory occupies 312Mb
  
-In corpora directory, you will find a simple py script for building a corpora from a file where every line is a document. Afterwards I used the following command:<file bash>​infomap-build -m /​net/​data/​CL/​projects/​wordspace/​software_tests/​corpora/​infoCorpus/​directory.txt firstModel</​file>​  +{{:software:​vizinfo2.png|}}
-directory.txt is a file contaning the name of every file contaning a document.+
  
 +In order to access the models, the standard command is<file bash>​associate [<​options>​] <​model>​ <​word></​file>​
 +Among the option, it is possible to obtain a word vector, the nearest neighbors of a word, or the word-document vector. Consider:<​file bash>​associate -m <​pathToTargetModel>​ -d -i d -n 10 document_100.txt
 +document_100.txt:​1.000000
 +document_80694.txt:​0.925041
 +document_162763.txt:​0.919077
 +document_95383.txt:​0.917450
 +document_176694.txt:​0.915522
 +document_155572.txt:​0.914388
 +document_197410.txt:​0.912332
 +document_101202.txt:​0.909776
 +document_144550.txt:​0.909703
 +document_164895.txt:​0.908825
 +</​file>​
 +This command retrieves the information from the model in <​pathToTargetModel>,​ in particular, the output should be again 10 (-n 10 ) documents (-d ), the input should be a document (- i d ). The input is the document '​document_100.txt'​. (In the server you would find the document in '​./​infoCorpus'​). After performing <file bash>​associate -m <​pathToTargetModel>​ -w -i d -n 10 document_100.txt</​file>​
 +i.e., looking for words instead of document close to '​document_100.txt'​ the result was:<​file bash>​seemingly:​0.731527
 +angry:​0.699753
 +kid:​0.693340
 +girlfriend:​0.676348
 +jake:​0.658571
 +boyfriend:​0.656249
 +scare:​0.652340
 +vicious:​0.651290
 +feel:​0.649538
 +bizarre:​0.643888</​file>​
 +This turned out to be the entry of Kubricks film "The Clock Work Orange"​ :-). The most related document corresponds to the film  [[http://​www.youtube.com/​watch?​v=tcSMDqXT52s|"​Pretty in Pink"​]]
 +An interesting option provided by Infomap is to install a model. This option is preferred for fina results, which should be available to several users. Following the manual, installing a model is not much more than moving a selected number of files from a non-installed model directory to a directory available system-wide. This option is intended to keep intermediate and final results apart.