lionel.duboeuf at boozter
Feb 8, 2010, 9:13 AM
Post #5 of 5
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Re: Document Frequency for a set of documents
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Thanks ard for your response,i found it usefull.
regards.
lionel
Ard Schrijvers a écrit :
> crossposting to the user list as I think this issue belongs there. See
> my comments inline
>
> On Fri, Feb 5, 2010 at 10:27 AM, lionel duboeuf
> <lionel.duboeuf [at] boozter> wrote:
>
>> Hi,
>>
>> Sorry for asking again, **I still have not found a scalable solution to get
>> the document frequency of a term t according a set of documents. Lucene only
>> store the document frequency for the global corpus, but i would like to be
>> able to get the document frequency of a term according only to a subset of
>> documents (i.e. a user's collection of documents).
>>
>> I guess that querying the index to get the number of hits for each term and
>> for each field, filtered by a user will be to slow.
>> Any idea ?
>>
>
> I have recently developed out-of-the-box faceted navigation exposed
> over jcr (hippo repository on top of jackrabbit) where I think you are
> looking for efficient faceted navigation as well, right? First of all,
> I am also interested if others have something to add to my findings.
>
> First of all, you can approach your issue in two different angles,
> where I think depending on the number of results vs number of terms
> (unique facets), you can best switch (runtime) between the two
> approaches:
>
> Approach (1): The lucene TermEnum is leading: if the lucene field has
> *many* (say more then 100.000) unique values, it becomes slow (and
> approach two might be better)
>
> You have a BitSet matchingDocs, and you want the count for all the
> terms for field 'brand' where of course one of the documents in
> matchingDocs should have the term:
> Suppose your field is thus 'brand', then you can do:
>
> TermEnum termEnum = indexReader.terms(new Term("brand", ""));
> // iterate through all the values of this facet and see
> look at number of hits per term
>
> try {
> TermDocs termDocs = indexReader.termDocs();
> // open termDocs only once, and use seek: this is more efficient
> try {
> do {
> Term term = termEnum.term();
> int count = 0;
> if (term != null && term.field() ==
> internalFacetName) { // interned comparison
>
> termDocs.seek(term);
> while (termDocs.next()) {
> if (matchingDocs.get(termDocs.doc())) {
> count++;
> }
> }
> if (count > 0) {
> if (!"".equals(term.text())) {
>
> facetValueCountMap.put(term.text(), new Count(count));
> }
> }
>
> } else {
> break;
> }
> } while (termEnum.next());
> } finally {
> termDocs.close();
> }
> } finally {
> termEnum.close();
> }
>
> Approach (2): matching docs are leading. All lucene fields that should
> be useable for your facet counts, must be indexed with TermVectors.
> This approach becomes slow when the matching docs grow > 100.000 hits.
> Then, you rather use approach (1)
>
> Create your own HitCollector, and have its hit method something like:
>
> public final void collect(final int docid, final float score) {
> try {
> if (facetMap != null) {
> final TermFreqVector tfv =
> reader.getTermFreqVector(docid, internalName);
> if (tfv != null) {
> for (int i = 0; i < tfv.getTermFrequencies().length; i++) {
> addToFacetMap(tfv.getTerms()[i]);
> }
>
>
> Note that the HitCollector's are not advised for large hit sets, also see [1]
>
> This is how i currently have a really performant faceted navigation
> exposed as a jcr tree. If somebody has tried more ways, or something
> to add, I would be interested
>
> Regards Ard
>
> [1] http://lucene.apache.org/java/2_3_2/api/org/apache/lucene/search/HitCollector.html
>
>
>> regards,
>>
>> Lionel
>>
>> *
>> *
>>
>>
>>
>>
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