ab at getopt
Mar 29, 2012, 2:14 AM
Post #5 of 7
(558 views)
Permalink

Re: delete entries from posting list Lucene 4.0
[In reply to]


On 27/03/2012 20:25, Zeynep P. wrote: > While using the pruning package, I realised that ridf is calculated in > RIDFTermPruningPolicy as follows: > Math.log(1  Math.pow(Math.E, termPositions.freq() / maxDoc))  df > > However, according to the original paper (Blanco et al.) for residual idf, > it should be log(df/D) + log (1  e^(**tf/D)). Thus, in the equation, > Math.pow should be Math.pow(Math.E,  (termPositions.freq() / maxDoc)) > > Do I miss something in the calculation or is this a bug? Hmm, good question! After checking the original paper again, and then checking our implementation, I think that this is indeed a bug, and we should add the minus there, but ... this formula may be completely broken either way. The paper that you mention (http://www.dc.fi.udc.es/~barreiro/publications/blanco_barreiro_ecir2007.pdf) says thus: "Residual idf is defined in [3] as the difference between the observed idf (IDF ) and the idf expected under the assumption that the terms follow an independence model, such as Poisson (IDF^). [...] If tf is the total number of tokens for a term t, then the ridf devised by a Poisson distribution is RIDF = IDF − IDF^ = −log(df/D) + log(1 − e^(tf/D)) [2] " Since the purpose of the RIDF metric is to select informative words collectionwide, and not perdocument, then it makes sense that they use a collectionwide metric like IDF as a baseline vs. another collectionwide metric based on total term frequency, or rather the total number of term occurrences in a collection. The problem in our implementation is that we use a withindocument term frequency (the number of occurrences of t in the current document) and not a collectionwide term frequency... so, it looks to me that the fix would be to first fully traverse the doc enumeration and calculate the total number of term occurrences in all documents (e.g. in RIDFTermPruningPolicy.initPositionsTerm(..) ), and use this value in the formula in place of termPositions.freq().  Best regards, Andrzej Bialecki <>< ___. ___ ___ ___ _ _ __________________________________ [__  ____/__\/ Information Retrieval, Semantic Web _____ \   Embedded Unix, System Integration http://www.sigram.com Contact: info at sigram dot com  To unsubscribe, email: javauserunsubscribe [at] lucene For additional commands, email: javauserhelp [at] lucene
