Jake,

I converted the ids to integers with rowid, and then
modified InMemoryCollapsedVariationBayes0.loadVectors() such that it
returns a SparseMatrix (instead of SparseRowMatrix) whose row ids are keys
from <IntWritable, VectorWritable> tf vectors. I am not sure if it works,
since the values of mapped integer ids (results of rowid) are in the range
[0, #ofDocuments), but I
believe it does.

Constructing SparseMatrix needs RandomAccessSparseVector as row vectors and
tf-vectors are sparse vectors, so I assumed that an incoming tf vector
itself, or getDelegate if it is a NamedVector, can be cast to
RandomAccessSparseVector.
I will submit the diff tomorrow, so you can review and commit.

Thank you for your help.


On Mon, Aug 6, 2012 at 8:19 PM, Jake Mannix <[email protected]> wrote:

> Hi Gokhan,
>
>   This looks like a bug in the
> InMemoryCollapsedVariationBayes0.loadVectors()
> method - it takes the SequenceFile<? extends Writable, VectorWritable> and
> ignores
> the keys, assigning the rows in order into an in-memory Matrix.
>
>   If you run "$MAHOUT_HOME/bin/mahout rowid -i <your tf-vector-path> -o
> <output path>"
> this converts Text keys into IntWritable keys (and leaves behind an index
> file, a mapping
> of Text -> IntWritable which tells you which int is assigned to which
> original text key).
>
>   Then what you'd want to do is modify
> InMemoryCollapsedVariationBayes0.loadVectors()
> to actually use the keys which are given to it, instead of reassigning to
> sequential
> ids.  If you make this change, we'd love to have the diff - not too many
> people use
> the cvb0_local path (it's usually used for debugging and testing smaller
> data sets to see that topics are converging properly), but getting it to
> actually produce
> document -> topic outputs which correlate with original docIds would be
> very nice! :)
>
> On Mon, Aug 6, 2012 at 4:00 AM, Gokhan Capan <[email protected]> wrote:
>
> > Hi,
> >
> > My question is about interpreting lda document-topics output.
> >
> > I am using trunk.
> >
> > I have a directory of documents, each of which are named by integers, and
> > there is no sub-directory of the data directory.
> > The directory structure is as follows
> > $ ls /path/to/data/
> >    1
> >    2
> >    5
> >    ...
> >
> > From those documents I want to detect topics, and output:
> > - topic - top terms
> > - document - top topics
> >
> > To this end, I first run seqdirectory on the directory:
> > $ mahout seqdirectory -i $DIR_IN -o $SEQDIR -c UTF-8 -chunk 1
> >
> > Then I run seq2sparse to create tf vectors of documents:
> > $ mahout seq2sparse -i $SEQDIR -o $SPARSEDIR --weight TF --maxDFSigma 3
> > --namedVector
> >
> > After creating vectors, I run cvb0_local on those tf-vectors:
> > $ mahout cvb0_local -i $SPARSEDIR/tf-vectors -do $LDA_OUT/docs -to
> > $LDA_OUT/words -top 20 -m 50 --dictionary $SPARSEDIR/dictionary.file-0
> >
> > And to interpret the results, I use mahout's vectordump utility:
> > $ mahout vectordump -i $LDA_OUT/docs -o $LDA_HR_OUT/docs --vectorSize 10
> > -sort true -p true
> >
> > $ mahout vectordump -i $LDA_OUT/words -o $LDA_HR_OUT/words --dictionary
> > $SPARSEDIR/dictionary.file-0 --dictionaryType sequencefile --vectorSize
> 10
> > -sort true -p true
> >
> > The resulting words file consists of #ofTopics lines.
> > I assume each line is in <topicID \t wordsVector> format, where a
> > wordsVector is a sorted vector whose elements are <word, score> pairs.
> >
> > The resulting docs file on the other hand, consists of #ofDocuments
> lines.
> > I assume each line is in <documentID \t topicsVector> format, where a
> > topicsVector is a sorted vector whose elements are <topicID, probability>
> > pairs.
> >
> > The problem is that the documentID field does not match with the original
> > document ids. This field is populated with zero-based auto-incrementing
> > indices.
> >
> > I want to ask if I am missing something for vectordump to output correct
> > document ids, or this is the normal behavior when one runs lda on a
> > directory of documents, or I make a mistake in one of those steps.
> >
> > I suspect the issue is seqdirectory assigns Text ids to documents, while
> > CVB algorithm expects documents in another format, <IntWritable,
> > VectorWritable>. If this is the case, could you help me for assigning
> > IntWritable ids to documents in the process of creating vectors from
> them?
> > Or should I modify the o.a.m.text.SequenceFilesFromDirectory code to do
> so?
> >
> > Thanks
> >
> > --
> > Gokhan
> >
>
>
>
> --
>
>   -jake
>



-- 
Gokhan

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