问题
Association mining seems to give good results for retrieving related terms in text corpora. There are several works on this topic including well-known LSA method. The most straightforward way to mine associations is to build co-occurrence matrix of docs X terms and find terms that occur in the same documents most often. In my previous projects I implemented it directly in Lucene by iteration over TermDocs (I got it by calling IndexReader.termDocs(Term)). But I can't see anything similar in Solr.
So, my needs are:
- To retrieve the most associated terms within particular field.
- To retrieve the term, that is closest to the specified one within particular field.
I will rate answers in the following way:
- Ideally I would like to find Solr's component that directly covers specified needs, that is, something to get associated terms directly.
- If this is not possible, I'm seeking for the way to get co-occurrence matrix information for specified field.
- If this is not an option too, I would like to know the most straightforward way to 1) get all terms and 2) get ids (numbers) of documents these terms occur in.
回答1:
You can export a Lucene (or Solr) index to Mahout, and then use Latent Dirichlet Allocation. If LDA is not close enough to LSA for your needs, you can just take the correlation matrix from Mahout, and then use Mahout to take the singular value decomposition.
I don't know of any LSA components for Solr.
回答2:
Since there are still no answers to my questions, I have to write my own thoughts and accept it. Nevertheless, if someone propose better solution, I'll happily accept it instead of mine.
I'll go with co-occurrence matrix, since it is the most principal part of association mining. In general, Solr provides all needed functions for building this matrix in some way, though they are not as efficient as direct access with Lucene. To construct matrix we need:
- All terms or at least the most frequent ones, because rare terms won't affect result of association mining by their nature.
- Documents where these terms occur, again, at least top documents.
Both these tasks may be easily done with standard Solr components.
To retrieve terms TermsComponent or faceted search may be used. We can get only top terms (by default) or all terms (by setting max number of terms to take, see documentation of particular feature for details).
Getting documents with the term in question is simply search for this term. The weak point here is that we need 1 request per term, and there may be thousands of terms. Another weak point is that neither simple, nor faceted search do not provide information about the count of occurrences of the current term in found document.
Having this, it is easy to build co-occurrence matrix. To mine association it is possible to use other software like Weka or write own implementation of, say, Apriori algorithm.
回答3:
You can get the count of occurrences of the current term in found document in the following query:
http://ip:port/solr/someinstance/select?defType=func&fl=termfreq(field,xxx),*&fq={!frange l=1}termfreq(field,xxx)&indent=on&q=termfreq(field,xxx)&sort=termfreq(field,xxx) desc&wt=json
来源：https://stackoverflow.com/questions/7393908/what-is-the-easiest-way-to-implement-terms-association-mining-in-solr