Managing Ranking Profiles
- Rialto Administrator
- Super Selector
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Creating ranking profiles. When creating profiles, check out the Ranking Boosts and Best Practices to Creating Ranking Profiles sections, to make sure that your ranking is strong.
Creating a Ranking Profile
You can create a new ranking profile, or you can duplicate an existing profile and edit its boosts, and then save it as a new profile.
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On the Ranking List page (Market > Manage Profiles and Rankings > Ranking Profiles), select Add Ranking. The Ranking Name Placeholder page appears.
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On the right-hand side, enter the name and description for your ranking profile.
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Select the ranking boosts. For more information about boosts, see Ranking Boosts.
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To adjust the boost weight, select the circle under the weight you want to assign - low, medium, or high. Offers matching boost with the 'High' weight will be shown higher in relation to offers matching boost with the 'Low' weight.
Only the boost that you included in the profile will affect the ranking of offers in the feed. Boosts that you did not include in the profile will not affect the ranking.
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To delete a boost, hover your cursor over the line, and select the 'X' to remove the line.
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To add additional boost , select Add Criteria.
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Click Save to save the ranking profile. You are directed to the Ranking List page, where you will find your new ranking profile. You can now associate this profile with the recommendations feed profile (see Creating a Recommendations Feed Profile).
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From the Ranking List (Market > Manage Profiles and Rankings > Ranking Profiles) page, select Duplicate in the row actions list on the profile you wish to duplicate. The profile is duplicated.
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The name of your new ranking profile starts with “Copy of ….”. Change that to a meaningful name.
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Edit the boost of the profile as necessary.
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Click Save to save the profile. You are directed to the Ranking List page, where you will find your new ranking profile. You can now associate this profile with the recommendations feed profile (see Creating a Recommendations Feed Profile).
Editing a Ranking Profile
Any changes you make to the ranking profiles are propagated to the staff. When next opening the feed, your staff will see the resulting changes to their feeds.
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From the Ranking List (Market > Manage Profiles and Rankings > Ranking Profiles), select Edit in the row actions list of the profile.
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On the page of the selected ranking profile, add, remove, or change the boosts, and modify their weights.
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If desired, change the name and the description of the profile.
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Click Save to save and return to the Recommendations Profile List page.
Ranking Boosts
Each boost has two characteristics: whether it's scaling or fixed, and whether it's work-level or offer-level.
A scaling boost adds more to an offer based on how closely it aligns with the category, up to the same amount of a fixed boost. A fixed boost adds a flat amount based on whether it matches value configured. For example, "Total sales" will add more boost the more overall sales a title has had, capping out at the same amount as a fixed boost. "Readership level" will add a flat amount if an offer matches the readership level configured.
A work-level boost applies equally to all offers within a group, and is an indication of the content of the resource. Work-level boosts can be used to sort the overall order of works in a feed. Offer-level boosts apply to specific offers in a work group and can be used to prioritize which offer to recommend. As a rule, use a medium or high weight on work-level boosts, but low weight on offer-level boosts. This will sort feeds first based on best-fit content for your collection, then choose the best offer from within a group based on your policies.
| Ranking Boosts | Description |
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Fixed, offer-level boosts that will promote offers that are available as DDA, ATO, DRM free, and Downloadable.
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| Format | Fixed, offer-level boost that will promote offers available as Ebook or Print. |
| High usage across all institutions | A scaling, work-level boost to works with the highest usage among Rialto customers over the past 36 months. |
| High usage trend across all institutions | A scaling, work-level boost to works with upward trending usage among Rialto customers. Using machine learning, trending is calculated evaluating usage changes for works, in order to focus on works with significantly increasing usage over a shorter period of time. |
| Historical usage at your institution | A scaling work-level boost to offers with high usage from your institution. |
| License | A fixed, offer-level boost to your preferred electronic license to promote in results. Choose as many or as few licenses as you like. |
| Lowest Price | A scaling, offer-level boost for offers with the lowest listing price. |
| Newest Edition | A scaling, offer-level boost that combines curated edition data provided by the New Titles team and machine learning to identify and promote the most recent edition of a work. |
| Platform | A fixed, offer-level boost to your preferred electronic platform to promote in results. Choose as many or as few as you like. |
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Predicted global usage |
A scaling, work level boost for titles based on predicted trending usage drawn from all Rialto libraries. |
| Predicted to be of interest to your institution | A scaling, work-level boost for works that combines the "Predicted to be Popular" and "Historical usage at your intuition" boosts. This will promote works in results that are not only projected to sell well, but may also be of interest to your institution. |
| Predicted to be Popular (Predicted Sales) | A scaling, work-level boost for works with the likelihood to have high sales. Using machine learning, this signal evaluates the similarity of a work to works that have been popular in the past across Rialto and Oasis. |
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Predicted usage in your institution |
A scaling, work-level boost for titles based on predicted trending usage drawn from the local institution. |
| ProQuest enhanced records | A fixed, offer-level boost to offers with records treated by the ProQuest New Titles team. |
| Recently Published | A scaling, work-level boost for works that have been published within the current year; promoting titles based on how recently they have been published. |
| Recent Sales | A scaling, work-level boost for works that have the highest recent sales across Rialto and Oasis within the last ninety days. |
| Readership Level | A fixed, work-level boost to the readership levels you choose to promote in results. Select as many or as few levels as you like. Note that works of fiction all have a readership level of general audience. |
| Top Publishers (beta) | A scaling, offer-level boost that promotes offers sold by the top five-hundred best-selling publishers based on the past three years of ProQuest's approval plan sales. |
| Total Sales |
A scaling, work-level boost for works that have the highest overall sales (since 2013).
The total sales are calculated based on historical sales data across Rialto and Oasis for works. The information is updated monthly.
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Best Practices to Creating Ranking Profiles
Follow the below recommendations to make sure the ranking provides proper visibility to content that is attractive to your institution, and that you do not miss potential offers.
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Give high or medium weight to scaling title-level boosts--this will sort feeds first based on content.
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Give low weight to offer-level boosts. They will act as tie-breakers among offers with the same content rank. The tie-breaking element acts as the differentiating factor and boosts one offer over another. These boosts can be used to prioritize specific offers based on your institutional policies.
Rialto Default Ranking Profile
The following ranking profile is provided with Rialto out-of-the-box. This profile is general and permissive, and allows the selection staff to do their work in the first weeks after Rialto integration, before the institutional profiles are finalized.
You can modify the profile as you would like or leave it as-is while you are creating the institutional profiles.
| Profile | High Weight | Medium Weight | Low Weight |
|---|---|---|---|
| Recent popular | Predicted to be popular | Recently published | |
| Usage and predicted fit | Historical usage at your institution |
Predicted to be popular Recently published Predicted to be of interest to your institution |
Deleting a Ranking Profile
You cannot delete any ranking profile associated with a selection plan. You will see a notification when attempting to do so. If you desire to remove the profile, you will need to access the selection plan in question, swap ranking profiles there, and save the plan. Once the profile has been removed, it can be deleted.
However, you can delete a ranking profile even when it is used in any of your staff’s feeds. If you delete such a profile, the feed results will not immediately change. When next opening the feed, the Ranking drop-down no longer shows the name of the deleted ranking profile, but is replaced by the general word 'Ranking'. However, the boost of the deleted ranking profile still applies. Advise your staff to select an alternative ranking and save their feed.
You can delete a single recommendation feed or several feeds in one action.
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On the Ranking List page (Market > Manage Profiles and Rankings > Ranking Profiles), check one or more profiles that you would like to delete.
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Select Remove Selected above the list. The profiles are removed.