Statistical Popularity Badges
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-Statistical Popularity Badges allow libraries to set popularity parameters that define popularity badges, which bibliographic records can earn if they meet the set criteria. Popularity badges can be based on factors such as circulation and hold activity, bibliographic record age, or material type. The popularity badges that a record earns are used to adjust catalog search results to display more popular titles (as defined by the badges) first. Within the OPAC there is a new sort option called "Sort by Popularity" which will allow users to sort records based on the popularity assigned by the popularity badges.
+Statistical Popularity Badges allow libraries to set popularity parameters that define popularity badges, which bibliographic records can earn if they meet the set criteria. Popularity badges can be based on factors such as circulation and hold activity, bibliographic record age, or material type. The popularity badges that a record earns are used to adjust catalog search results to display more popular titles (as defined by the badges) first. Within the OPAC there are two new sort options called "Most Popular" and "Popularity Adjusted Relevance" which will allow users to sort records based on the popularity assigned by the popularity badges.
Popularity Rating and Calculation
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Popularity badge parameters define the criteria a bibliographic record must meet to earn the badge, as well as which bibliographic records are eligible to earn the badge. For example, the popularity parameter "Circulations Over Time" can be configured to create a badge that is applied to bibliographic records for DVDs. The badge can be configured to look at circulations within the last 2 years, but assign more weight or popularity to circulations from the last 6 months.
-Multiple popularity badges may be applied to a bibliographic record. For each applicable popularity badge, the record will be rated on a scale of 1-5, where a 5 indicates the most popularity. Evergreen will then assign an overall popularity rating to each bibliographic record by averaging all of the popularity badge points earned by the record. The popularity rating is stored with the record and will be used to rank the record within search results when the popularity badge is within the scope of the search. The popularity badges are recalculated on a regular and configurable basis by a cron job. Popularity badges can also be recalculated by an administrator directly on the server.
+Multiple popularity badges may be applied to a bibliographic record. For each applicable popularity badge, the record will be rated on a scale of 1-5, where a 5 indicates the most popular. Evergreen will then assign an overall popularity rating to each bibliographic record by averaging all of the popularity badge points earned by the record. The popularity rating is stored with the record and will be used to rank the record within search results when the popularity badge is within the scope of the search. The popularity badges are recalculated on a regular and configurable basis by a cron job. Popularity badges can also be recalculated by an administrator directly on the server.
Creating Popularity Badges
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* *Importance Scale:* The Importance Scale can be used to assign additional importance to events that occurred within the most recent Importance Interval. For example, if the Importance Horizon is '6 months' and the Importance Interval is '1 month', the Importance Scale can be set to '6' to indicate that events that happened within the last month will count 6 times, events that happened 2 months ago will count 5 times, etc. The Importance Scale should be entered as a number followed by 'day(s)', 'week(s)', 'month(s)', 'year(s)', such as '6 months' or '2 years'.
-* *Percentile:* Can be used to assign a badge to only the records that score above a certain percentile. For example, it can be used indicate that only want to assign the badge to records in the top 5% of results by setting the field to '95'. To optimize the popularity badges, percentile should be set between 95-99 to assign a badge to the top 5%-1% of records.
+* *Percentile:* Can be used to assign a badge to only the records that score above a certain percentile. For example, it can be used indicate that you only want to assign the badge to records in the top 5% of results by setting the field to '95'. To optimize the popularity badges, percentile should be set between 95-99 to assign a badge to the top 5%-1% of records.
* *Attribute Filter:* Can be used to assign a badge to records that contain a specific Record Attribute. Currently this field can be configured by running a report (see note below) to obtain the JSON data that identifies the Record Attribute. The JSON data from the report output can be copied and pasted into this field. A new interface for creating Composite Record Attributes will be implemented with future development of the web client.
** To run a report to obtain JSON data for the Attribute Filter, use SVF Record Attribute Coded Value Map as the template Source. For Displayed Fields, add Code, ID, and/or Description from the Source; also display the Definition field from the Composite Definition linked table. This field will display the JSON data in the report output. Filter on the Definition from the Composite Definition liked table and set the Operator to 'Is not NULL'.
Within the stock OPAC template there is a new option for sorting search results called "Most Popular". Selecting "Most Popular" will first sort the search results based on the popularity rating determined by the popularity badges and will then apply the default "Sort by Relevance". This option will maximize the popularity badges and ensure that the most popular titles appear higher up in the search results.
-There is a second new sort option called "Popularity Adjusted Relevance" that can be turned on by editing the ctx.popularity_sort setting in the OPAC template configuration. The "Popularity Adjusted Relevance" sort option can be used to find a balance between popularity and relevance in search results. For example, it can help ensure that records that are popular, but not necessarily relevant to the search, do not supersede records that are both popular and relevant in the search results. It does this by sorting search results using an adjusted version of Relevance sorting. When sorting by relevance, each bibliographic record is assigned a baseline relevance score between 0 and 1, with 0 being not relevant to the search query and 1 being a perfect match. With "Popularity Adjusted Relevance" the baseline relevance is adjusted by a scaled version of the popularity rating assigned to the bibliographic record. The scaled adjustment is controlled by a Global Flag called "Maximum Popularity Importance Multiplier" (MPIM). The MPIM takes the average popularity rating of a bibliographic record (1-5) and creates a scaled adjustment that is applied to the baseline relevance for the record. The adjustment can be between 1.0 and the value set for the MPIM. For example, if the MPIM is set to 1.2, a record with an average popularity badge score of 5 (maximum popularity) would have its relevance multiplied by 1.2—in effect giving it the maximum increase of 20% in relevance. If a record has an average popularity badge score of 2.5, the baseline relevance of the record would be multiplied by 1.1 (due to the popularity score scaling the adjustment to half way between 1.0 and the MPIM of 1.2) and the record would receive a 10% increase in relevance. A record with a popularity badge score of 0 would be multiplied by 1.0 (due to the popularity score being 0) and would not receive a boost in relevance.
+There is a second new sort option called "Popularity Adjusted Relevance", which can be used to find a balance between popularity and relevance in search results. For example, it can help ensure that records that are popular, but not necessarily relevant to the search, do not supersede records that are both popular and relevant in the search results. It does this by sorting search results using an adjusted version of Relevance sorting. When sorting by relevance, each bibliographic record is assigned a baseline relevance score between 0 and 1, with 0 being not relevant to the search query and 1 being a perfect match. With "Popularity Adjusted Relevance" the baseline relevance is adjusted by a scaled version of the popularity rating assigned to the bibliographic record. The scaled adjustment is controlled by a Global Flag called "Maximum Popularity Importance Multiplier" (MPIM). The MPIM takes the average popularity rating of a bibliographic record (1-5) and creates a scaled adjustment that is applied to the baseline relevance for the record. The adjustment can be between 1.0 and the value set for the MPIM. For example, if the MPIM is set to 1.2, a record with an average popularity badge score of 5 (maximum popularity) would have its relevance multiplied by 1.2—in effect giving it the maximum increase of 20% in relevance. If a record has an average popularity badge score of 2.5, the baseline relevance of the record would be multiplied by 1.1 (due to the popularity score scaling the adjustment to half way between 1.0 and the MPIM of 1.2) and the record would receive a 10% increase in relevance. A record with a popularity badge score of 0 would be multiplied by 1.0 (due to the popularity score being 0) and would not receive a boost in relevance.
Popularity Badge Example
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projects / Evergreen.git / commitdiff