From: kgs Date: Wed, 9 Sep 2009 17:21:44 +0000 (+0000) Subject: Moving to sysadmin folder. X-Git-Url: https://old-git.evergreen-ils.org/?a=commitdiff_plain;h=38ffddffb9963008336287807e313750b5e6fdd4;p=working%2Frandom.git Moving to sysadmin folder. git-svn-id: svn://svn.open-ils.org/ILS-Contrib/evergreen-ils.org@670 6d9bc8c9-1ec2-4278-b937-99fde70a366f --- diff --git a/docs/1.6/book1/sysadmin/indexedfieldweighting.xml b/docs/1.6/book1/sysadmin/indexedfieldweighting.xml new file mode 100644 index 000000000..565a5021c --- /dev/null +++ b/docs/1.6/book1/sysadmin/indexedfieldweighting.xml @@ -0,0 +1,233 @@ + +
+ 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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diff --git a/docs/indexedfieldweighting.xml b/docs/indexedfieldweighting.xml deleted file mode 100644 index 565a5021c..000000000 --- a/docs/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. -
-
- 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 - - - -
-
-
- 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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