I have a database of product information indexed by name, type, manufacturer, etc. Users often submit search queries whose results would be contained neatly in one or more facets. When this situation arises, I would like for Solr to parse the query and apply the relevant facets.
For example, searching shoes should return results in the shoe category. More ambitiously, searching plaid shirt should query plaid on items in the shirt category.
Is it possible to configure Solr to do this?
Thanks in advance.
Asking Solr to do what you want is a tall order. Your best bet would be to store categories in a field that is weighted very highly. For example, if you have a category field with the value of "shoes", having a hit on that field will increase the relevance of documents on that category, thus having them show up first. Same goes for the second example.
As for faceting, your question is not clear on how you want to apply faceting.
Related
I have a document which has title, stockCode, category fields.
I have different field types (and analysis chains) for each. For instance title has EdgeNGram 2 to 20, category has EdgeNGram 3 to 10 with different range and stockCode just has lowercase filter.
So that, I don't want to search from documents with keyword "sample" with building the query like title:sample OR stockCode:sample OR category:sample.
I'd like to search with just "q=sample".
I copied my fields to text but It does not work. Because all fields analyzed as same. But I don't want to index stockCode as EdgeNGram or any other filters. I'd like to index my fields as I configured and I'd like to search a keyword over them base on my indexes.
I've been researching about that for three days, and Solr has a little bit poor documentation.
You can use the edismax handler, as this will allow you to give a list of fields to query and supply the query by itself. You can also give separate weights to each field for scoring them differently.
defType=edismax&q=sample&qf=title^10 stockCode category
.. will search for sample in each of the three fields, giving a 10x boost to any hits in the title field.
You can find the documentation about the edismax query parser under Searching in the reference guide.
I want to build a smart search with Algolia. The point is to use keywords to rank the results. Lets say user types "smarphone blue cheap good camera". This should find all blue smarthones and order them by price and camera characteristics.
The idea is to somehow map those keywords to a ranking formula.
Doea any one know if it is possible with Algolia and if so what is the best way to achieve the desired result?
To automatically detect and filter by facet values (like blue, good camera), you could use Query Rules, in particular Dynamic Filtering.
However, that shouldn't be necessary. If you include the color (containing for instance the blue value) and characteristics (containing for instance the good camera value) attributes in your searchableAttributes list, then the search request will return relevant results based on purely textual relevance matched in those attributes.
On the other hand, sorting strategies impact the Algolia indices at build time, therefore in order to change the sorting strategy based on the query (e.g. sort results by ascending price if the search query contains cheap), you will need to setup a new replica index for which results are sorted by price. On the frontend, when detecting a relevant keyword (e.g. cheap), you can decide to switch the search queries to the primary index or to the sorted replica.
I understood the reason for having search profile and boosting results based on some fields e.g. distance, rating, etc. To me, that's most likely applicable to structured documents like json files. The scenario that I cannot make sense of it is when indexer gets search service index let's say a MS Word or PDF document in azure blob. We have two entries of "id" and "content" which I don't know how the search score would apply to it.
For e.g. there are two documents with different contents. I searched for a keyword and the same keyword found in two documents resulted into getting two different scores for two MS Word documents. My challenge is why this score should be different while both documents contain the same keyword?
The score is determined by many factors, for example, the count of terms in each document, and the number of searchable fields in which query terms were found. In your example, the documents have different lengths, so naturally they'll have different scores. HTH.
Suppose, I have 1000 sellers (S1.....S1000) of Apparels listed on my site. Since all the sellers are paying some amount to me, I am giving them equal weight-age, and the results are shown based on relevancy.
Now, I am planning to start with premium service, where I am thinking to list one supplier on top for each keywords in search results. Let say, S1 has been given premium search for keywords 'Jeans', so if a user searches 'jeans', I first wants to display this supplier on the top, then display other supplier based on relevancy. Plus, this premium service is for only for one month. So, another supplier say S2 can avail this service in next month and so on.
Is there any plugin, wherein I can store which supplier should be shown for which keyword. I am even OK with making 2 queries to meet the desire results.
Please suggest
I think the Query Elevation Component is your friend, you can configure which documents (and hence which suppliers) come first for any given query, see
https://wiki.apache.org/solr/QueryElevationComponent
If that's too much work, you could also add a new boolean field in your documents, indicating whether the document is to be promoted or not, and in the query, sort by this field first (so promoted documents come on top), and by score next (so most relevant documents come right after the promoted ones).
You can maybe also use the reRanking Componant :
https://cwiki.apache.org/confluence/display/solr/Query+Re-Ranking
With using a query like this :
q=jean&rq={!rerank reRankQuery=$rqq reRankDocs=1000 reRankWeight=3}&rqq=(brand:S1)
The top 1000 of results from query jean will be re-ranking thanks to the boost (of 3) add to the documents which contain the field brand with the value S1.
It can be useful, but in your case I think the QueryElevationComponent is the best.
Be careful, reRanking is only available since version 4.9.
I've recently started experimenting with Solr. My data is indexed and searchable. My problem is in the sorting. I have three fields: Author, Title, Sales.
I would like to search against the author & title fields, but have the sales value influence the score so that matches with higher sales move toward the top, even if the initial match score is not the highest.
Simply sorting by sales does not produce valid results as a result with a near 0 score for the search term, but a lot of sales in general could end up above a perfect match for the term that has never been sold.
I am seeing results that, while great term matches, are not necessarily the product I want showing at the top of the list.
If you're using the dismax handler, you can add a boost function (bf) with the field you want to boost on, e.g.
http://...?q=foo&bf="fieldValue(sales)^1.5"
...to make the value of the sales figure give a bump. You can, of course, make the function more complex if you want to munge the sales data in some way.
More info is easily found.
You may also just want to do this at index time since the sales data isn't going to be changing on the fly.
You can also use Index-time boosting.
And here's detailed info on using function queries to influence scoring.