From 5d12be8b91bc0bcb16a3aa692fc9d8d38c14de5d Mon Sep 17 00:00:00 2001 From: kgs Date: Wed, 9 Sep 2009 17:23:41 +0000 Subject: [PATCH] Oh wait. This is for the HTML for these, not the XML. That goes into the other repository. I need to repeat all of this in the other repo. git-svn-id: svn://svn.open-ils.org/ILS-Contrib/evergreen-ils.org@671 6d9bc8c9-1ec2-4278-b937-99fde70a366f --- docs/1.6/book1/sysadmin/indexedfieldweighting.xml | 233 ---------------------- 1 file changed, 233 deletions(-) delete mode 100644 docs/1.6/book1/sysadmin/indexedfieldweighting.xml diff --git a/docs/1.6/book1/sysadmin/indexedfieldweighting.xml b/docs/1.6/book1/sysadmin/indexedfieldweighting.xml deleted file mode 100644 index 565a502..0000000 --- a/docs/1.6/book1/sysadmin/indexedfieldweighting.xml +++ /dev/null @@ -1,233 +0,0 @@ - -
- Indexed-Field and Matchpoint Weighting - - - This chapter describes indexed field weighting and matchpoint weighting, which - control relevance ranking in Evergreen catalog search results. - - - In tuning search relevance, it is good practice to make incremental - adjustments, capture search logs, and assess results before making further - adjustments. - - - - -
- Indexed-field Weighting - Indexed-field weighting is configured in the Evergreen database in the weight column - of the config.metabib_field table, which follows the other four columns in this table: - field_class, name, xpath, and format. - The following is one representative line from the config.metabib_field table: - author | conference | - //mods32:mods/mods32:name[@type='conference']/mods32:namePart[../mods32:role/mods32:roleTerm[text()='creator']] - | mods32 | 1 ) - The default value for index-field weights in config.metabib_field is 1. Adjust the - weighting of indexed fields to boost or lower the relevance score for matches on that - indexed field. The weight value may be increased or decreased by whole integers. - For example, by increasing the weight of the title-proper field from 1 to 2, a search - for jaguar would double the relevance for the book - titled Aimee and Jaguar than for a record with the - term jaguar in another indexed field. -
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- Matchpoint Weighting - Matchpoint weighting provides another way to fine-tune Evergreen relevance ranking, - and is configured through floating-point multipliers in the multiplier column of the - search.relevance_adjustment table. - Weighting can be adjusted for one, more, or all multiplier fields in - search.relevance_adjustment. - You can adjust the following three matchpoints: - - - - first_word - boosts relevance if the query is one term long and matches the - first term in the indexed field (search for twain, get a bonus for twain, - mark but not mark twain) - - - - word_order - increases relevance for words matching the order of search terms, - so that the results for the search legend - suicide would match higher for the book Legend of a Suicide than for the book, Suicide Legend - - - - full_match - boosts relevance when the full query exactly matches the entire - indexed field (after space, case, and diacritics are normalized). So a title - search for The Future of Ice would get a - relevance boost above Ice Ages of the - Future. - - - Here are the default settings of the search.relevance_adjustment table: - - search.relevance_adjustment table - - - - field_class - name - bump_type - multiplier - - - - - author - conference - first_word - 1.5 - - - author - corporate - first_word - 1.5 - - - author - other - first_word - 1.5 - - - author - personal - first_word - 1.5 - - - keyword - keyword - word_order - 10 - - - series - seriestitle - first_word - 1.5 - - - series - seriestitle - full_match - 20 - - - title - abbreviated - first_word - 1.5 - - - title - abbreviated - full_match - 20 - - - title - abbreviated - word_order - 10 - - - title - alternative - first_word - 1.5 - - - title - alternative - full_match - 20 - - - title - alternative - word_order - 10 - - - title - proper - first_word - 1.5 - - - title - proper - full_match - 20 - - - title - proper - word_order - 10 - - - title - translated - first_word - 1.5 - - - title - translated - full_match - 20 - - - title - translated - word_order - 10 - - - title - uniform - first_word - 1.5 - - - title - uniform - full_match - 20 - - - title - uniform - word_order - 10 - - - -
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- Combining Index Weighting and Matchpoint Weighting - Index weighting and matchpoint weighting may be combined. The relevance boost of the - combined weighting is equal to the product of the two multiplied values. - If the relevance setting in the config.metabib_field were increased to 2, and the - multiplier set to 1.2 in the search.relevance_adjustment table, the resulting matchpoint - increase would be 240%. - - In practice, these weights are applied serially -- first the index weight, then - all the matchpoint weights that apply -- because they are evaluated at different - stages of the search process. - -
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