X-Git-Url: http://jsfdemo.indexdata.com/?a=blobdiff_plain;f=src%2Frelevance.c;h=a365ebd91a369c6f1e4336c003e784ba47a0f6d4;hb=ab485834bd7708fbdd8e896a7548da22a33fed87;hp=7603a7a928c2422941e9f5340fe89b55d266cf51;hpb=beda9709478c02182ceadb5f0526c32d8986c039;p=pazpar2-moved-to-github.git diff --git a/src/relevance.c b/src/relevance.c index 7603a7a..a365ebd 100644 --- a/src/relevance.c +++ b/src/relevance.c @@ -1,5 +1,5 @@ /* This file is part of Pazpar2. - Copyright (C) 2006-2009 Index Data + Copyright (C) 2006-2012 Index Data Pazpar2 is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free @@ -21,42 +21,29 @@ Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA #include #endif +#include #include #include #include "relevance.h" -#include "pazpar2.h" +#include "session.h" struct relevance { int *doc_frequency_vec; int vec_len; struct word_entry *entries; - pp2_charset_t pct; + pp2_charset_token_t prt; NMEM nmem; }; - struct word_entry { const char *norm_str; int termno; + char *ccl_field; struct word_entry *next; }; -static void add_word_entry(NMEM nmem, - struct word_entry **entries, - const char *norm_str, - int term_no) -{ - struct word_entry *ne = nmem_malloc(nmem, sizeof(*ne)); - ne->norm_str = nmem_strdup(nmem, norm_str); - ne->termno = term_no; - - ne->next = *entries; - *entries = ne; -} - - int word_entry_match(struct word_entry *entries, const char *norm_str) { for (; entries; entries = entries->next) @@ -67,73 +54,136 @@ int word_entry_match(struct word_entry *entries, const char *norm_str) return 0; } -static struct word_entry *build_word_entries(pp2_charset_t pct, NMEM nmem, - const char **terms) +void relevance_countwords(struct relevance *r, struct record_cluster *cluster, + const char *words, int multiplier, const char *name) { - int termno = 1; /* >0 signals THERE is an entry */ - struct word_entry *entries = 0; - const char **p = terms; - - for (; *p; p++) - { - pp2_relevance_token_t prt = pp2_relevance_tokenize(pct, *p); - const char *norm_str; + int *mult = cluster->term_frequency_vec_tmp; + const char *norm_str; + int i, length = 0; - while ((norm_str = pp2_relevance_token_next(prt))) - add_word_entry(nmem, &entries, norm_str, termno); + pp2_charset_token_first(r->prt, words, 0); + for (i = 1; i < r->vec_len; i++) + mult[i] = 0; - pp2_relevance_token_destroy(prt); + while ((norm_str = pp2_charset_token_next(r->prt))) + { + int res = word_entry_match(r->entries, norm_str); + if (res) + { + assert(res < r->vec_len); + mult[res] += multiplier; + } + length++; + } - termno++; + for (i = 1; i < r->vec_len; i++) + { + if (length > 0) /* only add if non-empty */ + cluster->term_frequency_vecf[i] += (double) mult[i] / length; + cluster->term_frequency_vec[i] += mult[i]; } - return entries; + + cluster->term_frequency_vec[0] += length; } -void relevance_countwords(struct relevance *r, struct record_cluster *cluster, - const char *words, int multiplier) +static void pull_terms(struct relevance *res, struct ccl_rpn_node *n) { - pp2_relevance_token_t prt = pp2_relevance_tokenize(r->pct, words); - - const char *norm_str; - - while ((norm_str = pp2_relevance_token_next(prt))) + char **words; + int numwords; + char *ccl_field; + int i; + + switch (n->kind) { - int res = word_entry_match(r->entries, norm_str); - if (res) - cluster->term_frequency_vec[res] += multiplier; - cluster->term_frequency_vec[0]++; + case CCL_RPN_AND: + case CCL_RPN_OR: + case CCL_RPN_NOT: + case CCL_RPN_PROX: + pull_terms(res, n->u.p[0]); + pull_terms(res, n->u.p[1]); + break; + case CCL_RPN_TERM: + nmem_strsplit(res->nmem, " ", n->u.t.term, &words, &numwords); + for (i = 0; i < numwords; i++) + { + const char *norm_str; + + ccl_field = nmem_strdup_null(res->nmem, n->u.t.qual); + + pp2_charset_token_first(res->prt, words[i], 0); + while ((norm_str = pp2_charset_token_next(res->prt))) + { + struct word_entry **e = &res->entries; + while (*e) + e = &(*e)->next; + *e = nmem_malloc(res->nmem, sizeof(**e)); + (*e)->norm_str = nmem_strdup(res->nmem, norm_str); + (*e)->ccl_field = ccl_field; + (*e)->termno = res->vec_len++; + (*e)->next = 0; + } + } + break; + default: + break; } - pp2_relevance_token_destroy(prt); } -struct relevance *relevance_create(pp2_charset_t pct, - NMEM nmem, const char **terms) +struct relevance *relevance_create_ccl(pp2_charset_fact_t pft, + NMEM nmem, struct ccl_rpn_node *query) { - struct relevance *res = nmem_malloc(nmem, sizeof(struct relevance)); - const char **p; + struct relevance *res = nmem_malloc(nmem, sizeof(*res)); int i; - for (p = terms, i = 0; *p; p++, i++) - ; - res->vec_len = ++i; - res->doc_frequency_vec = nmem_malloc(nmem, res->vec_len * sizeof(int)); - memset(res->doc_frequency_vec, 0, res->vec_len * sizeof(int)); res->nmem = nmem; - res->entries = build_word_entries(pct, nmem, terms); - res->pct = pct; + res->entries = 0; + res->vec_len = 1; + res->prt = pp2_charset_token_create(pft, "relevance"); + + pull_terms(res, query); + + res->doc_frequency_vec = nmem_malloc(nmem, res->vec_len * sizeof(int)); + for (i = 0; i < res->vec_len; i++) + res->doc_frequency_vec[i] = 0; return res; } +void relevance_destroy(struct relevance **rp) +{ + if (*rp) + { + pp2_charset_token_destroy((*rp)->prt); + *rp = 0; + } +} + void relevance_newrec(struct relevance *r, struct record_cluster *rec) { if (!rec->term_frequency_vec) { - rec->term_frequency_vec = nmem_malloc(r->nmem, r->vec_len * sizeof(int)); - memset(rec->term_frequency_vec, 0, r->vec_len * sizeof(int)); + int i; + + // term frequency [1,..] . [0] is total length of all fields + rec->term_frequency_vec = + nmem_malloc(r->nmem, + r->vec_len * sizeof(*rec->term_frequency_vec)); + for (i = 0; i < r->vec_len; i++) + rec->term_frequency_vec[i] = 0; + + // term frequency divided by length of field [1,...] + rec->term_frequency_vecf = + nmem_malloc(r->nmem, + r->vec_len * sizeof(*rec->term_frequency_vecf)); + for (i = 0; i < r->vec_len; i++) + rec->term_frequency_vecf[i] = 0.0; + + // for relevance_countwords (so we don't have to xmalloc/xfree) + rec->term_frequency_vec_tmp = + nmem_malloc(r->nmem, + r->vec_len * sizeof(*rec->term_frequency_vec_tmp)); } } - void relevance_donerecord(struct relevance *r, struct record_cluster *cluster) { int i; @@ -151,7 +201,7 @@ void relevance_prepare_read(struct relevance *rel, struct reclist *reclist) int i; float *idfvec = xmalloc(rel->vec_len * sizeof(float)); - reclist_rewind(reclist); + reclist_enter(reclist); // Calculate document frequency vector for each term. for (i = 1; i < rel->vec_len; i++) { @@ -171,7 +221,6 @@ void relevance_prepare_read(struct relevance *rel, struct reclist *reclist) } } // Calculate relevance for each document - while (1) { int t; @@ -181,15 +230,12 @@ void relevance_prepare_read(struct relevance *rel, struct reclist *reclist) break; for (t = 1; t < rel->vec_len; t++) { - float termfreq; - if (!rec->term_frequency_vec[0]) - break; - termfreq = (float) rec->term_frequency_vec[t] / rec->term_frequency_vec[0]; + float termfreq = (float) rec->term_frequency_vecf[t]; relevance += 100000 * (termfreq * idfvec[t] + 0.0000005); } - rec->relevance = relevance; + rec->relevance_score = relevance; } - reclist_rewind(reclist); + reclist_leave(reclist); xfree(idfvec); }