问题
I have thousand of pages in website which I parsed and stored it as Inverted Index viz
document
- docid (PK,FK)
- url
- charactercount
- wordcount
Charactercount and wordcount helps me determine long document from short which I may use later.
word
- wordid (PK,FK)
- word
- doc_freq
- inverse_doc_freq
For inverse_doc_freq calculation I use fictional high number (100000000) to prevent total document recalculation.
loc
- wordid
- docid
- word_freq
- weight
(wordid & docid combined unique)
The weight is a score calculated on simple basis like word in title + word in url + word frquency etc.
I am having problem framing my sql query for search words. For 3 word search I am doing like
- Break query into each word
- Check inverse_doc_freq for each word and remove low idf word (removal of stop word)
- stem the remaining word (assume still 3 words remain)
- Query for each word
It is at stage 4 that I am getting stuck ! My SQL query is like
SELECT d.docid,url,inverse_doc_freq,word_freq,weight from document d,word w,loc l WHERE d.docid=l.docid AND w.wordid=l.wordid AND (word='word1' OR word='word2' OR word='word3') ORDER BY weight DESC
The returned documents are not correct though. Trust I might have to Search thrice to find documents for each word and then try to find the common documents, but how ? Is it possible to use only 1 MySQL query for it ? Also is it possible to use TF-IDF and how ?
回答1:
You need to aggregate at the document level.
select d.docid, d.url, sum(weight) as weight
from document d join
loc l
on d.docid = l.docid join
word w
on w.wordid = l.wordid
where w.word in ('word1', 'word2', 'word3')
group by d.docid
order by weight DESC;
来源:https://stackoverflow.com/questions/23539380/mysql-query-of-inverted-index-data