Right now getstream passes down ordinal score but not the actual internal score which makes it difficult to debug. I tried reading the api docs and inspecting the response but don't see anything. I'm also not quite sure how their own internal explorer works. When pressing "preview" the results set is limited and makes fine tuning difficult.
Our API call only returns an integer that orders the items. If you want the actual score, go to your organization's dashboard, click on your app, and click on the name of your ranking under the Ranking Methods header. then click on the "Preview Changes" you will see the ranked feed with the full score based on the ranking algorithm. There's also a search bar there if you want to change the feed and user_id values. I don't know if putting the actual score in the feed is on our roadmap but I can bring it up with the team.
Related
I'm using the Bing Ads Python SDK and I'm trying to get an ad report showing the cost data for each ad for each day.
I can successfully query the AdPerformanceReportRequest service and get all the ads and their metrics back.
But I'm getting back all ads with any activity on them, including impressions. I only want rows where cost > 0.
The filter objects are specific to the report type, not to the metric and none of the examples in the SDK Github repo show how to do this.
The Google Ads API lets us specify a where clause in our report query (Where cost > 0). How can I do this with the Bing Ads API?
Do I have to download all the data and filter myself (this report is quite large, about 100Mb, and about 75% smaller when filtered)? Or is there a more efficient way to do this by not requesting those rows that are useless to me at all?
Any point in the right direction would be very much appreciated.
Edit: As was pointed out below, this is not currently possible. A tip if you're trying to filter yourself locally is that the metrics in the in-memory report object record is a string. So if you want to filter out zero values, you need to filter out values that are string representations of '0.00', not '0' or the integer value 0.
The reporting service via Bing Ads API does not support such a filter. I suggest please vote on this related feature request and append comments / details about your scenario as needed. Thank you.
Is there some way to slow down or disable the dynamic search that occurs on master data fields in transaction screens? For example, when looking up a customer or item on a sales order the system will start to search for a customer or item if you pause or type slow. Several of our clients have found the live search to cause errors because the wrong item is chosen when the search list pops up or the list can be confusing for a user who types slow.
Thanks,
Kurt
Case in point: say we have a search query that returns 2000 results ranging from very relevant to hardly relevant at all. When this is sorted by relevance this is fine, as the most relevant results are listed on the first page.
However, when sorting by another field (e.g. user rating) the results on the first page are full of hardly-relevant results, which is a problem for our client. Somehow we need to only show the 'relevant' results with highest ratings.
I can only think of a few solutions, all of which have problems:
1 - Filter out listings on Solr side if relevancy score is under a threshold. I'm not sure how to do this, and from what I've read this isn't a good idea anyway. e.g. If a result returns only 10 listings I would want to display them all instead of filter any out. It seems impossible to determine a threshold that would work across the board. If anyone can show me otherwise please show me how!
2 - Filter out listings on the application side based on score. This I can do without a problem, except that now I can't implement pagination, because I have no way to determine the total number of filtered results without returning the whole set, which would affect performance/bandwidth etc... Also has same problems of the first point.
3 - Create a sort of 'combined' sort that aggregates a score between relevancy and user rating, which the results will then be sorted on. Firstly I'm not sure if this is even possible, and secondly it would be weird for the user if the results aren't actually listed in order of rating.
How has this been solved before? I'm open to any ideas!
Thanks
If they're not relevant, they should be excluded from the result set. Since you want to order by a dedicated field (i.e. user rating), you'll have to tweak how you decide which documents to include in the result at all.
In any case you'll have to define "what is relevant enough", since scores aren't really comparable between queries and doesn't say anything about "this was xyz relevant!".
You'll have to decide why those documents that are included aren't relevant and exclude them based on that criteria, and then either use the review score as a way to boost them further up (if you want the search to appear organic / by relevance). Otherwise you can just exclude them and sort by user score. But remember that user score, as an experience for the user, is usually a harder problem to make relevant than just order by the average of the votes.
Usually the client can choose different ordering options, by relevance or ratings for example. But you are right that ordering by rating is probably not useful enough. What you could do is take into account the rating in the relevance scoring. For example, by multiplying an "organic" score with a rating transformed as a small boost. In Solr you could do this with Function Queries. It is not hard science, and some magic is involved. Much is common sense. And it requires some very good evaluation and testing to see what works best.
Alternatively, if you do not want to treat it as a retrieval problem, you can apply faceting and let users do filtering of the results by rating. Let users help themselves. But I can imagine this does not work in all domains.
Engineers can define what relevancy is. Content similarity scoring is not only what constitutes relevancy. Many Information Retrieval researchers and engineers agree that contextual information should be used besides only the content similarity. This opens a plethora of possibilities to define a retrieval model. For example, what has become popular are Learning to Rank (LTR) approaches where different features are learnt from search logs to deliver more relevant documents to users given their user profiles and prior search behavior. Solr offers this as module.
I'm using Azure Search on my e-commerce site, and now i faced the problem with paging on my search page. When i reload the search page i can get different order of products. So when i'm using paging i can see same products on different pages, and this is critical.
I started researching what's going wrong, and i've found this info on Microsoft docs https://learn.microsoft.com/en-us/rest/api/searchservice/add-scoring-profiles-to-a-search-index#what-is-default-scoring
Search score values can be repeated throughout a result set. For
example, you might have 10 items with a score of 1.2, 20 items with a
score of 1.0, and 20 items with a score of 0.5. When multiple hits
have the same search score, the ordering of same scored items is not
defined, and is not stable. Run the query again, and you might see
items shift position. Given two items with an identical score, there
is no guarantee which one appears first.
So if i got it correctly, i face this issue because products has same score.
How to fix this?
You got it correctly! Because the products you are getting have the same score, there is no guarantee which one appears first.
In order to avoid it in this stage, you can add to your $orderby parameter a field that has unique values, and that way you guarantee the same order. However, this approach doesn’t take scoring into account. We are currently working on a solution to this problem. We will update this answer once the solution is available (the ETA at this point is weeks, not months).
Please note that you can now use search.score() function to order by score:
From the link below:
https://learn.microsoft.com/en-us/rest/api/searchservice/odata-expression-syntax-for-azure-search.
"You can specify multiple sort criteria. The order of expressions determines the final sort order. For example, to sort descending by score, followed by rating, the syntax would be $orderby=search.score() desc,rating desc."
I'm trying to organize a solr search engine. I've already set up the misspelling system and the suggestions.
However I can't seem to find how to retrieve the top 10 most searched words/terms/keywords in solr/lucene. How can I get this? I want to display those on my homepage.
Solr does not provide this kind of feature out of the box. There is the StatsComponent, that provides you with all kind of statistics, but all of those are numeric only.
Depending on how you access solr (directly or via your own app) you could intercept all calls an log the query string. I did this in a recent project where I logged a queries to a database. If you submit all keywords to an other core on your solr server, you can faceting queries on your search terms as described by Hyque
You could use a facet for retrieving the Top X words like this:
http://yourservergoeshere/solr/select?q=*&wt=xml&indent=true&facet=true&facet.query=*&facet.field=message&facet.limit=10&facet.minCount=1
The value of facet.field depends on the field you like to search in. With facet.limit you'll (obviously) limit the amount of results to 10. You'll find the facet results at the end of the results, starting with "facet_counts"
Edit: I really should go to bed earlier. I didn't see the "most searched" in your question. Sorry for that.
Apache Solr does not provide any such capability as of today. There is a desire for this and a JIRA ticket corresponding to it. You can vote for it if you'd like to see it in Solr some day: https://issues.apache.org/jira/browse/SOLR-10359.
The stats component provides information around statistics, but it's mostly numeric in nature. You could parse server logs and come up with a way to build a Frequently Searched Terms (e.g. pump those logs in SiLK or Kibana for visualization).
If you have the ability to change the front end and add some javascript code to the UI or can intercept the search request and make an async or batch calls to APIs for tracking, you can use SearchStax Analytics that provides Search Analytics that tracks searches, clicks, cart actions, revenue, etc.