The solr syntax for fuzzy search is:
q~n where q is the query term and n is the Levenshtein Distance (e.g. 1-3).
The syntax for prefix search is:
q* where q is a query term and the * indicates a wildcard.
Combining both like q~n* (with even n=1) has the side effect, that nearly everything matches
(for a reason, that i still need to find out).
Combining both like q*~n (with even n=1) has the side effect, that the query performs as it will be a prefix search only.
In our use case we need to offer suggestions based on historical queries stored in index. That seam also to be the thing google does when you type in a misspelled term, and it is a great solution for suggestions.
The problem is, we can either offer suggestions wich start with the same index or some with a defined Levenshtein Distance <= 3 which is impracticable when it comes to long terms.
Now, I know that there is a similar question asked 3 years ago, where the solution says it aint possible to express in solr syntax and the whole case does not make any particular sense, but in my opinion it makes sense and a combination would be a perfekt solution to practical problems.
Not a tested solution, did you think of using this ? q* OR q~1 for example name:S* OR name: S~1 ,
Larger example : name:Samson~3 OR name:Samson* returned : <str name="name">Samsung SpinPoint P120 SP2514N - hard drive - 250 GB - ATA-133</str></doc>
I have not tried this specifically, but it looks like you might be able to do what you want with the ComplexPhraseQueryParser.
It looks like the ComplexPhraseQueryParser is slated to be distributed with 4.8, but for now you can get the plugin (there are install instructions in the zip files) from Solr's Jira. https://issues.apache.org/jira/browse/SOLR-1604
There is some discussion using distance here. http://lucene.472066.n3.nabble.com/ComplexPhraseQueryParser-and-wildcards-td2742244.html
I would expect with the ComplexPhraseQueryParser you could do a query like "q*"~n.
Related
I'm looking for a way to limit the effect (or eliminate it) of "keyword stuffing" in SOLR. (We're currently running a SOLR 6.2.0 server).
I've tried setting omitTermFreqAndPositions="true", but when I do that, some queries throw phrase query errors (specifically queries with search terms such as G1966B - likely due to word splitting and such). I could go down the road of disabling the word splitting and try to avoid the phrase query errors, but this is simply going to mess up more things than I'm trying to fix.
Does anyone have any suggestions on how to limit the affect of multiple keyword matches in a single field?
Example: If we have a description field with something like this:
BrandX 1200 Series G1924B LC/MSD SL XBC System.
This BrandX 1200 Series G1924B ( G 1924 B , G1924 B , G 1924B ) LC/MSD SL XBC >System is in excellent condition.
When someone does a search for "G1924B" I would like to avoid scoring this document higher just because it happens to have G1924B (or a variation of that) in there several times.
In theory someone could repeat the keyword many times in their description to try to trick the system into ranking their search results higher.
Any suggestions?
Thanks!
This happens to appear as a more frequent requirement than initially thought.
If you remove both term freq and positions, you lose phrase search capability.
I would recommend to write a custom similarity that ignores TF ( Term Frequency).
At the moment the default BM25 take TF in consideration.
You can just pick that class and adjust the similarity calculus to consider TF as a constant.
e.g.
org.apache.lucene.search.similarities.BM25Similarity.BM25DocScorer#score
[1] org.apache.lucene.search.similarities.BM25Similarity
I have successfully implemented a Czech lemmatizer for Lucene. I'm testing it with Solr and it woks nice at the index time. But it doesn't work so well when used for queries, because the query parser doesn't provide any context (words before or after) to the lemmatizer.
For example the phrase pila vodu is analyzed differently at index time than at query time. It uses the ambiguous word pila, which could mean pila (saw e.g. chainsaw) or pít (the past tense of the verb "to drink").
pila vodu ->
Index time: pít voda
Query time: pila voda
.. so the word pila is not found and not highlighted in a document snippet.
This behaviour is documented at the solr wiki (quoted bellow) and I can confirm it by debugging my code (only isolated strings "pila" and "vodu" are passed to the lemmatizer).
... The Lucene QueryParser tokenizes on white space before giving any text to the Analyzer, so if a person searches for the words sea biscit the analyzer will be given the words "sea" and "biscit" seperately, ...
So my question is:
Is it possible to somehow change, configure or adapt the query parser so the lemmatizer would see the whole query string, or at least some context of individual words? I would like to have a solution also for different solr query parsers like dismax or edismax.
I know that there is no such issue with phrase queries like "pila vodu" (quotes), but then I would lose the documents without the exact phrase (e.g. documents with "pila víno" or even "pila dobrou vodu").
Edit - trying to explain / answer following question (thank you #femtoRgon):
If the two terms aren't a phrase, and so don't necessarily come together, then why would they be analyzed in context to one another?
For sure it would be better to analyze only terms coming together. For example at the indexing time, the lemmatizer detects sentences in the input text and it analyzes together only words from a single sentence. But how to achieve a similar thing at the query time? Is implementing my own query parser the only option? I quite like the pf2 and pf3 options of the edismax parser, would I have to implement them again in case of my own parser?
The idea behind is in fact a bit deeper because the lemmatizer is doing word-sense-disambiguation even for words that has the same lexical base. For example the word bow has about 7 different senses in English (see at wikipedia) and the lemmatizer is distinguishing such senses. So I would like to exploit this potential to make searches more precise -- to return only documents containing the word bow in the concrete sense required by the query. So my question could be extended to: How to get the correct <lemma;sense>-pair for a query term? The lemmatizer is very often able to assign the correct sense if the word is presented in its common context, but it has no chance when there is no context.
Finally, I implemented my own query parser.
It wasn't that difficult thanks to the edismax sources as a guide and a reference implementation. I could easily compare my parser results with the results of edismax...
Solution :
First, I analyze the whole query string together. This gives me the list of "tokens".
There is a little clash with stop words - it is not that easy to get tokens for stop words as they are omitted by the analyzer, but you can detect them from PositionIncrementAttribute.
From "tokens" I construct the query in the same way as edismax do (e.g. creating all 2-token and/or 3-token phrase queries combined in DisjunctionMaxQuery instances).
I am trying to set up Solr but encountered the problem mentioned in the title. I just downloaded Solr and used the built-in example. When I used a query with words occurred in the example documents, such as "ipod". Solr worked properly. However, when I added some words that are not in these documents, such as "what". Solr does not return anything. For me, it is weird since the relevance scores should be computed to query terms separately and added up. Non-existing query term should not affect the ranking (even though the coord norm is affected, thus the scores of documents will change).
Could anyone tell me what might be the issue? Thanks.
There are several ways of configuring how you want this behavior. I'll assume that you're using the edismax query handler for these examples, although some of these also apply to the standard lucene query parser.
The reason for not always wanting "ipod what" to retrieve the same subset sa "ipod" is that you'll get a poor result set and user experience for terms that are more general than "ipod" (i.e. searching for "microsoft windows" will not be perceived as a good search result if you're showing only general hits for anything about windows - it's usually better to say "we didn't find anything" in those cases). It all depends on your use case.
First, you can do it yourself, by applying either AND or OR between terms to get the exact kind of matching you're looking for.
You can use q.op to configure wether each term should be AND-ed together (all required) or OR-ed together (any one is sufficient). This overrides the (now deprecated) value from <solrQueryParser defaultOperator=".."/> in schema.xml.
For (e)dismax, there's the mm parameter, which allows you do more specific, but in a general way, handling of how you want matches to be performed. mm allows you to say "at least 50% of the terms should match" or "if there's only two terms, both should match, but any over that should be optional" or "match everything up to four, and 75% after that".
So right now I'm just using the admin interface to run search queries. I know that a tilde ~ suffix causes a word to become fuzzy search.
However, what about a phrase? I tried "some words"~ but it doesn't seem to be returning results when it should be. Any idea why? Do I need a special fieldtype or special filters?
Right now, everything is pretty vanilla but I did import a lot of data. (About 12 million rows). I know that there are things in there that should be getting returned with a good fuzzy match that are not.
Any help is appreciated.
Also, if it makes a difference I would like to use the levenshtein algorithm.
ComplexPhraseQueryParser can be used to handle wildcard and fuzzy phrase queries.
Is there a way to specify a set of terms that are more important when performing a search?
For example, in the following question:
"This morning my printer ran out of paper"
Terms such as "printer" or "paper" are far more important than the rest, and I don't know if there is a way to list these terms to indicate that, in the global knowledge, they'd have more weight than the rest of words.
For specific documents you can use QueryElevationComponent, which uses special XML file in which you place your specific terms for which you want specific doc ids.
Not exactly what you need, I know.
And regarding your comment about users not caring what's underneath, you control the final query. Or, in the worst case, you can modify it after you receive it at Solr server side.
Similar: Lucene term boosting with sunspot-rails
When you build the query you can define what are the values and how much these fields have weight on the search.
This can be done in many ways:
Setting the boost
The boost can be set by using "^ "
Using plus operator
If you define + operator in your query, if there is a exact result for that filed value it is shown in the result.
For a better understanding of solr, it is best to get familiar with lucene query syntax. Refer to this link to get more info.