Hi all, Lucene score document based on the correlation between the query q and document t: (this is raw function, I don't pay attention to the boost_t, coord_q_d factor)
score_d = sum_t( tf_q * idf_t / norm_q * tf_d * idf_t / norm_d_t) (*) Could anybody explain it in detail ? Or are there any papers, documents about this function ? Because: I have also read the book: Modern Information Retrieval, author: Ricardo Baeza-Yates and Berthier Ribeiro-Neto, Addison Wesley (Hope you have read it too). In page 27, they also suggest a scoring funtion for vector model based on the correlation between query q and document d as follow (I use different symbol): sum_t( weight_t_d * weight_t_q) score_d(d, q)= --------------------------------- (**) norm_d * norm_q where weight_t_d = tf_d * idf_t weight_t_q = tf_q * idf_t norm_d = sqrt( sum_t( (tf_d * idf_t)^2 ) ) norm_q = sqrt( sum_t( (tf_q * idf_t)^2 ) ) (**): sum_t( tf_q*idf_t * tf_d*idf_t) score_d(d, q)=--------------------------------- (***) norm_d * norm_q The two function, (*) and (***), have 2 differences: 1. in (***), the sum_t is just for the numerator but in the (*), the sum_t is for everything. So, with norm_q = sqrt(sum_t((tf_q*idf_t)^2)); sum_t is calculated twice. Is this right? please explain. 2. No factor that define norms of the document: norm_d in the function (*). Can you explain this. what is the role of factor norm_d_t ? One more question: could anybody give me documents, papers that explain this function in detail. so when I apply Lucene for my system, I can adapt the document, and the field so that I still receive the correct scoring information from Lucene . Best regard, Thanks every body, ===== Ð#7863;ng Nhân __________________________________ Do you Yahoo!? Yahoo! Mail - Find what you need with new enhanced search. http://info.mail.yahoo.com/mail_250 --------------------------------------------------------------------- To unsubscribe, e-mail: [EMAIL PROTECTED] For additional commands, e-mail: [EMAIL PROTECTED]