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.
Related
I'm using Solr 5 and need to remove stop words to prevent over-matching and avoid bloating the index with high IDF terms. However, the corpus includes a lot part numbers and name initials like "Steve A" and "123-OR-A". In those cases, I don't want "A" and "OR" to get removed by the stopword filter factory as they need to be searchable.
The Stanford POS tagger does a great job detecting that the above examples are nouns, not stop words, but is this the right approach for solving my problem?
Thanks!
Only you can decide whether this is the right approach. If you can integrate POS tagger in and it gives you useful results - that's good.
But just to give you an alternative, you could look at duplicating your fields and processing them differently. For example, if you see 123-OR-A being split and stopword-cleaned, that probably means you have WordDelimiterFilterFactory in your analyzer stack. That factory has a lot of parameters you could try tweaking. Or, you could copyField your content to another (store=false) field and process it without WordDelimiterFilterFactory all together. Then you search over both copies of your data, possibly with different boost for different fields.
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.
I'm using Solr 5.x, standard highlighter, and i'm getting snippets which matches even one of the search terms only, even if i indicate q.op=AND.
I need ONLY the fields and snippets that matches ALL the terms (unless i say q.op=OR or just omit it), i.e. the field/snippet must satisfy the query. Solr does return the field/snippet that has all the terms, but also return many others.
I'm using hl.fl=*, to get the only fields having the terms, and searching against the default field ('text' containing full doc). Need to use * since i have multiple dynamic fields. Most fields are 'text_general' type (for search and HL), and some are 'string' type for faceting.
If its not possible for snippets to have all the terms, i MUST get only the fields that satisfy the query fully (since the question is more talking about matching all the terms, but the search query can become arbitrarily complex, so the fields/snippets should match the query).
Also, next is to get snippets highlighted with proximity based search/terms. What should i do/use for this? The fields coming in highlighting in this scenario should also satisfy the proximity query (unlike i get a field that contain any term, without regard to proximity constrains and other query terms etc)
Thanks for your help.
I've also encountered the same problem with highlighting. In my case, the query like
(foo AND bar) OR eggs
highlighted eggs and foo despite bar was not present in the document. I didn't manage to come up with proper solution, however I devised a dirty workaround.
I use the following query:
id:highlighted_document_id AND text:(my_original_query)
with debugQuery set to true. Then I parse explain text for highlighted_document_id. The text contains the terms from the query, which have contributed to the score. The terms, which should not be highlighted, are not present in the explanation.
The Python regex expressions I use to extract the terms (valid for Solr 5.2.1):
term_regex = re.compile(r'weight\(text:(.+) in')
wildcard_term_regex = re.compile(r'text:(.+), product')
then I simply search the markings in the highlighted text and remove them if the term doesn't match against any of the term in term_regex and wildcard_term_regex.
The solution is probably pretty limited, but works for me.
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".
I would like to implement relevance feedback in Solr. Solr already has a More Like This feature: Given a single document, return a set of similar documents ranked by similarity to the single input document. Is it possible to configure Solr's More Like This feature to behave like More Like Those? In other words: Given a set of documents, return a list of documents similar to the input set (ranked by similarity).
According to the answer to this question turning Solr's More Like This into More Like Those can be done in the following way:
Take the url of the result set of the query returning the specified documents. For example, the url http://solrServer:8983/solr/select?q=id:1%20id:2%20id:3 returns the response to the query id:1 id:2 id:3 which is practically the concatenation of documents 1, 2, 3.
Put the above url (concatenation of the specified documents) in the url.stream GET parameter of the More Like This handler: http://solrServer:8983/solr/mlt?mlt.fl=text&mlt.mintf=0&stream.url=http://solrServer:8983/solr/select%3Fq=id:1%20id:2%20id:3. Now the More Like This handler treats the concatenation of documents 1, 2 and 3 as a single input document and returns a ranked set of documents similar to the concatenation.
This is a pretty bad implementation: Treating the set of input documents like one big document discriminates against short documents because short documents occupy a small portion of the entire big document.
Solr's More Like This feature is implemented by a variation of The Rocchio Algorithm: It takes the top 20 terms of the (single) input document (the terms with the highest TF-IDF values) and uses those terms as the modified query, boosted according to their TF-IDF. I am looking for a way to configure Solr's More Like This feature to take multiple documents as its input, extract the top n terms from each input document and query the index with those terms boosted according to their TF-IDF.
Is it possible to configure More Like This to behave that way? If not, what is the best way to implement relevance feedback in Solr?
Unfortunately, it is not possible to configure the MLT handler that way.
One way to do it would be to implement a custom SearchComponent and register it to a (dedicated) SearchHadler.
I've already done something similar and it is quite easy if you look a the original implementation of MLT component.
The most difficult part is the synchronization of the results from different shard servers, but it can be skipped if you do not use shards.
I would also strongly recommend to use your own parameters in your implementation to prevent collisions with other components.