Is it possible to boost a document on the indexing stage depending on the field value?
I'm indexing a text field pulled from the database. I would like to boost results that are shorter over the longer ones. So the value of boost should depend on the length of the text field.
This is needed to alter the standard SOLR behavior that in my case tends to return documents with multiple matches first.
Considering I have a field that stores the length of the document, the equivalent in the query of what I need at indexing would be:
q={!boost b=sqrt(length)}text:abcd
Example:
I have two items in the DB:
ABCDEBCE
ABCD
I always want to get ABCD first for the 'BC' query even though the other item contains the search query twice.
The other solution to the problem would be ability to 'switch off' the feature that scores multiple matches higher at query time. Don't know if that is possible either...
Doing this at index time is important as the hardware I run the SOLR on is not too powerful and trying to boost on query time returns with OutOfMemory Exception. (Even If I could work around that increasing memory for java I prefer to be on the safe side and implement the index the most efficient way possible.)
Yes and no - but how you do it depends on how you're indexing your documents.
As far as I know there's no way of resolving this only on the solr server side at the moment.
If you're using the regular XML based interface to submit documents, let the code that generates the submitted XML add boost=".." values to the field or to the document depending on the length of the text field.
You can check upon DIH Special Commands which has a $docBoost command
$docBoost : Boost the current doc. The value can be a number or the
toString of a number
However, there seems no $fieldBoost Command.
For you case though, if you are using DefaultSimilarity, shorter fields are boosted higher then longer fields in the Score calculation.
You can surely implement your own Simiarity class with a changed TF (Term Frequency) and LengthNorm Calculation as your needs.
Related
I have a filed 'qualification' which is having multiple values (something like MCA, MBA, MSC, PhD, ...).
My requirement is to display results in the order MSC, MCA, PhD, MBA. So, I am using the below query to boost the field values.
&bq=(qualification: "MSC"^5 "MCA"^4 "PhD"^3 "MBA"^2)
The above query is working only when I use q=*:*
But when search with any text like q=course, I am not getting the results with specified order.
Please help what I did wrong.
Thanks & Regards
Venu
You're probably not doing anything "wrong", but when you actually search for something, the score isn't flat (i.e. it's no longer just 1) any more.
If you don't want your query to affect the score, use a filter query (fq instead). This does however not give you any actual relevance inside the results - if you still want that, you'll probably have to adjust your boosts to be far higher, so that the actual scores are only used internally within each boost level.
&bq=qualification:"MSC"^50000
&bq=qualification:"MCA"^40000
&bq=qualification:"PhD"^30000
&bq=qualification:"MBA"^20000
If you append debugQuery=true to your query string, you can see how the score is calculated for each document, and adjust your boosts accordingly.
I'm attempting to query solr for documents, given a basic schema with the following field names, data types irrelevant:
I'm attempting to match documents that match at least one of the following:
occupation, name, age, gender but i want to OR them together
How do you OR together many terms, and enforce the document to match at least one?
This seems to be failing: +(name:Sarah age:24 occupation:doctor gender:male)
How do you convert a boolean expression into solr query syntax? I can't figure out the syntax with + and - and the default operator for OR.
Still I don't get your requirement but you just need to query like:
+(age:24 OR gender:male)
Or if you want data for multiple value in same field with OR condition like.
i.e. You get data of age:24 and age:25 both.
+(age:24 OR age:25 OR gender:male)
Then you can:
+(age:(24 25) OR gender:male)
If it is't your requirement, then let me know.
If you want to make it as simple as possible for the client, just go for the dismax[1] or edismax[2] query parser.
Specifically you can configure a request parameter called "qf" :
"The qf parameter introduces a list of fields, each of which is assigned a boost factor to increase or decrease that particular field’s importance in the query. For example, the query below:
qf=fieldOne^2.3 fieldTwo fieldThree^0.4
assigns fieldOne a boost of 2.3, leaves fieldTwo with the default boost (because no boost factor is specified), and fieldThree a boost of 0.4.
These boost factors make matches in fieldOne much more significant than matches in fieldTwo, which in turn are much more significant than matches in fieldThree." from the wiki
Then you can just pass a free text query, and it will be searched in the fields you specified, giving also different importance to each one, if necessary.
[1] https://lucene.apache.org/solr/guide/6_6/the-dismax-query-parser.html
[2] https://lucene.apache.org/solr/guide/6_6/the-extended-dismax-query-parser.html
I'm looking into the possibility of de-boosting a set of documents during
query time. In my application, when I search for e.g. "preferences", I want
to de-boost content tagged with ContentGroup:"Developer" or in other words,
push those content back in the order. Here's the catch. I've the following
weights on query fields and boost query on source
qf=text^6 title^15 IndexTerm^8
As you can see, title has a higher weight.
Now, a bunch of content tagged with ContentGroup:"Developer" consists of a
title like "Preferences.material" or "Preferences Property" or
"Preferences.graphics". The boost on title pushes these documents at the
top.
What I'm looking is to see if there's a way to deboost all documents that are
tagged with ContentGroup:"Developer" irrespective of the term occurrence is
text or title. I tried something like, but didn't make any difference.
Source:simplecontent^10 Source:Help^20 (-ContentGroup-local:("Developer"))^99
I'm using edismax query parser.
Any pointers will be appreciated.
Thanks,
Shamik
You're onto something with your last attempt, but you have to start with *:*, so that you actually have something to subtract the documents from. The resulting set of documents (those not matching your query) can then be boosted.
From the Solr Relevancy FAQ
How do I give a negative (or very low) boost to documents that match a query?
True negative boosts are not supported, but you can use a very "low" numeric boost value on query clauses. In general the problem that confuses people is that a "low" boost is still a boost, it can only improve the score of documents that match. For example, if you want to find all docs matching "foo" or "bar" but penalize the scores of documents matching "xxx" you might be tempted to try...
q = foo^100 bar^100 xxx^0.00001 # NOT WHAT YOU WANT
...but this will still help a document matching all three clauses score higher then a document matching only the first two. One way to fake a "negative boost" is to give a large boost to everything that does not match. For example...
q = foo^100 bar^100 (*:* -xxx)^999
NOTE: When using (e)dismax, people sometimes expect that specifying a pure negative query with a large boost in the "bq" param will work (since Solr automatically makes top level purely negative positive queries by adding an implicit ":" -- but this doesn't work with "bq", because of how queries specified via "bq" are added directly to the main query. You need to be explicit...
?defType=dismax&q=foo bar&bq=(*:* -xxx)^999
I implementing Solr search using an API. When I call it using the parameters as, "Chillout Lounge", it returns me the collection which are same/similar to the string "Chillout Lounge".
But when I search for "Chillout Lounge Box", it returns me results which don't have any of these three words.(in the DB there are values which have these 3 values, but they are not returned.)
According to me, Solr uses Fuzzy search, but when it is done it should return me some values, which will have at least one these value.
Or what could be the possible changes I should to my schema.XML, such that is would give me proper values.
First of all - "Fuzzy search" is a feature you'll have to ask for (by using ~ in standard Lucene query syntax).
If you're talking about regular searches, you can use q.op to select which operator to use. q.op=AND will make sure that all the terms match, while q.op=OR will make any document that contain at least one of the terms be returned. As long as you aren't using fq for this, the documents that match more terms should be scored higher (as the score will add up across multiple terms), and thus, be shown higher in the result set.
You can use the debug query feature in the web interface to see scores for each term for a document, and find out why the document was returned at all. If the document doesn't match any terms, it shouldn't be returned, unless you're asking for all documents to be returned.
Be aware that the analyzer chain defined for the field you're searching might affect what's considered a match and not.
You'll have to add a proper example to get a more detailed answer.
Let's say I have documents with two fields, A and B.
I'd like to use SOLR's MoreLikeThis, but with a twist: I'm most interested in boosting documents whose A field is like my model document's B field. (That is, extract MLT's 'interesting terms' from the model B field, but only collect MLT results based on the A field.)
I don't see a way to use the mlt.fl fields or mlt.qf boosts to achieve this effect in a single query. (It seems mlt.fl specifies fields used for both discovery of 'interesting terms' and matching to those terms.) Am I missing some option?
Or will I have to extract the 'interesting terms' myself and swap the 'field:term' details?
(Other ideas in this same vein appreciated as well.)
Two options I see are:
Use a copyField - index your original document with a copy of field A named B, and then query using B.
Extend MoreLikeThisHandler and change the fields you query.
The first option costs a bit of programming (mostly configuration changes) and some memory consumption. The second involves more programming but no memory footprint increase. Hope one of them suits your needs.
I now think there are two ways to achieve the desired effect (without customizing the MLT source code).
First option: Do an initial MLT query with the MLT handler, adding the parameter &mlt.interestingTerms=details. This includes the list of terms that were deemed interesting, ranked with their relative boosts. The usual behavior uses those discovered terms against the same mlt.fl fields to find similar documents. For example, the response will include something like:
"interestingTerms":
["field_b:foo",5.0,"field_b:bar",2.9085307,"field_b:baz",1.67070794]
(Since the only thing about this initial query that's interesting is the interestingTerms, throwing in an fq that rules out all docs could help it skip unnecessary scoring work.)
Explicitly re-composing that interestingTerms info into a new OR query field_a:foo^5.0 field_a:bar^2.9085307 field_a:baz^1.67070794 amounts to using the B field example text to find documents that are similar in field A, and may be mimicking exactly the kind of query default MLT does on its usual model field.
Second option: Grab the model document's actual field B text, and feed it directly as a ContentStream body, to be used in lieu of a query, for specifying the model document. Then target mlt.fl at field A for the sake of collecting similar results. For example, a fragment of the parameters might be …&stream.body=foo bar baz&mlt.fl=field_a&…. Again, the net effect being that model text originally from field_b is finding documents similar only in field_a.