Chris, That's what I did, for debugging. The query is "biology", and here's what the API tells me for term frequencies: biolog 15 biologi 31 biologist 4
I actually see 13 occurrences of "biologist" and "biologists", 64 occurrences of "biology", 27 occurrences of "biological". I see "inform 22" but the actual count of the word "information" in the document is 33. But "ioniz 7" is correct. I don't see much correlation between what the API is telling me and what I see in the actual document. Am I missing something? Thanks ________________________________ From: Chris Hostetter [mailto:[EMAIL PROTECTED] Sent: Tue 2/7/2006 4:10 PM To: java-user@lucene.apache.org Subject: Re: How to get mapping of query terms to number of their occurrences in a doc? A cursory reading of your code looks ok ... stemming shouldn't be an issue as long as your measure of success is comparing docs that match your orriginal query with the counts you get out. What i mean by that is that any stemming should have already been taken care of when your query object was constructed (either by you manually, or by QueryParser). the direct equals comparisons you are dong should be fine. have you tried adding logging of the raw term field/text and the freq counts you get back to see if that helps you spot the problem? : Date: Mon, 6 Feb 2006 14:34:05 -0800 : From: Dmitry Goldenberg <[EMAIL PROTECTED]> : Reply-To: java-user@lucene.apache.org : To: java-user@lucene.apache.org : Subject: How to get mapping of query terms to number of their occurrences : in a doc? : : Given a query, I want to be able to, for each query term, get the number of occurrences of the term. I have tried what I'm including below and it does not seem to provide reliable results. Seems to work fine with exact matching but as soon as stemming kicks in, all bets are off as to value of the number of occurrences returned. : : Any ideas, anyone? Can this be written in a simpler and/or more efficient way? : Thanks - : : int totalOccurrences = 0; : : reader = IndexReader.open(getDirectory(indexDirPath)); : HashSet terms = new HashSet(); : query.extractTerms(terms); : : TermFreqVector[] tfvs = reader.getTermFreqVectors(docId); : if (tfvs != null) { : : // For each term frequency vector (i.e. for each field) : for (int i = 0; i < tfvs.length; i++) { : String field = tfvs[i].getField(); : String[] strTerms = tfvs[i].getTerms(); : int[] tfs = tfvs[i].getTermFrequencies(); : : if (strTerms != null) { : : // For each term in the query : for (Iterator iter = terms.iterator(); iter.hasNext();) { : : Term term = (Term) iter.next(); : // For each term in the vector : for (int j = 0; j < strTerms.length; j++) { : : // If found the query term among the vector terms : if (field.equals(term.field()) && strTerms[j].equals(term.text())) { : : // Add the term frequency to the total : totalOccurrences += tfs[j]; : : } : } : } : } : } : } : -Hoss --------------------------------------------------------------------- To unsubscribe, e-mail: [EMAIL PROTECTED] For additional commands, e-mail: [EMAIL PROTECTED]
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