I have configured azure autocomplete API with all parameters. It gives results for normal keywords but when I tried with misspell keyword then it doesn't provide me expected results. Also, I have added UseFuzzyMatching=true while configuration.
eg. machine -> gives the expected results. If we try with magine then it provides 0 results from autocomplete API.
Please let me know if I'm missing any configurations to make Fuzzy workable.
I have data in my index that contains product description and comment fields 'Boormachine' or 'machine', also it provide me result in search API for this.
I have configured suggester while creation of index with the following source fields:
Comment, CommentSmall, Description,
ItemBrandDescription, Itemcode,
ItemGroupDescription,ItemSupplierCode,
SupplierCode
We have configured autocomplete API with this:
as I need to find for keyword suggestions not in group and brand name so excluded these two fields from search fields in configuration.
We can see fuzzy related configuration in autocomplete with UseFuzzyMatching flag. Please let me know if I am missing some configuration to work fuzzy in azure search autocomplete API.
For References click this Link
The behavior Azure Search is providing is correct.
Magine is a different term than machine, and probably it does not exist in your index, this is why you're getting 0 results. To enable Fuzzy Search you actually need to append the ~ symbol to the term, so your search will look like:
"search=magine~"
https://learn.microsoft.com/en-us/azure/search/query-lucene-syntax#bkmk_fuzzy
Related
If I may have missed this in some other area of SO please redirect me but I don't think this is a duped question.
I am using Azure Search with an index field called Title which is searchable and filterable using a Standard Lucerne Analyzer.
When using the built-in explorer, if I want to return all Job Titles that are explicitly named Full Stack Developer I can achieve it this way:
$filter=Title eq 'Full Stack Developer'&$count=true
But if I want to retrieve all the Job Titles using a wildcard to return all records having Full Stack in the name this way:
$filter=Title eq 'Full Stack*'&$count=true
The first 20 or so records returned are spot on, but after that point I get a mix of records that have absolutely nothing in common with the Title I specified in the query. My initial assumption was that perhaps Azure was including my specified Title performing an inclusive keyword search on the text as well.
Though I found a few instances where that hypothesis seemed to prove out, so many more of the records returned invalidated that altogether.
Maybe I don't understand fully the mechanics under the hood of Azure Search and so though my query appears to be valid; my expectation of the result is way off.
So how should my query look to perform a wildcard resulting to guarantee the words specified in the search to be included in the Titles returned, if this should be possible? And what would be the correct syntax to condition the return to accommodate for OR operators to be inclusive?
Azure Cognitive Search allows you to perform wildcard searches limited to specific fields only. To do so, you will need to specify the name of the fields in which you want to perform the search in searchFields parameter.
Your search URL in this case would be something like:
https://accountname.search.windows.net/indexes/indexname/docs?api-version=2020-06-30&searchFields=Title&search=Full Stack*
From the link here:
Does anyone know how to ensure we can return normal result as well as accented result set via the azure search filter. For e.g the below filter query in Azure search returns a name called unicorn when i check for record with name unicorn.
var result= searchServiceClient.Documents.SearchAsync<myDto>("*",new SearchParameters
{
SearchFields = new List<string> {"Name"},
Filter = "Name eq 'unicorn'"
});
This is all good but what i want is i want to write a filter such that it returns record named unicorn as well as record named únicorn (please note the first accented character) provided that both record exist.
This can be achieved when searching for such name via the search query using language or Standard ASCII folding search analyzer as mentioned in this link. What i am struggling to find out is how can we implement the same with azure filters?
Please let me know if anyone has got any solutions around this.
Filters are applied on the non-analyzed representation of the data, so I don’t think there’s any way to do any type of linguistic analysis on filters. One way to work around this is to manually create a field which only do lowercasing + asciifloding (no tokenization) and then search lucene queries that look like this:
"normal search query terms" AND customFilterColumn:"filtérValuèWithÄccents"
Basically the document would both need to match the search terms in any field AND also match the filter term in the “customFilterColumn”. This may not be sufficient for your needs, but at least you understand the art of the possible.
Using filters it won't work unless you specify in advance all the possibilities:
for example:
$filter=name eq 'unicorn' or name eq 'únicorn'
You'd better work with a different analyzer that will change accents to it's root form. As another possibility, you can try fuzzy search:
search=unicorn~&highlight=Name
I'm trying to implement Azure Search on Kentico 12. Following the article below.
https://docs.kentico.com/k12/configuring-kentico/setting-up-search-on-your-website/using-azure-search/integrating-azure-search-into-pages
However, I have multiple indexes defined on the smart search not just a single index code name that I can hard code and also cannot aford to hard code index fields. Is there any tutorial out there that I can follow?
It sounds as if you're referring to building an Azure Search web part, is this correct. If so, make a property in your web part which allows you to select the code name from a list in the database. Secondly, regarding field names, you should be using generic field names like DocumentName, NodeAliaspath, etc. Although if you have very specific search results that need to be displayed, simply put in a switch statement to get the field names based on a class name.
I am using Solr 6.0.0
I am using data-driven-configuration for my configuration related purpose. Most of the configuration is standard.
I have a document in Solr with
name:"aquickbrownfox"
Now if I do a fuzzy search like:
name:aquickbrownfo~0.7
OR
name:aquickbrownf~0.7
It lists out the record in the results.
But if I do a search like:
name:aquickbrown~0.7
It does not list the record.
Does it have to do something with the maxEdits in solrconfig.xml which is set to 2 ?
I tried increasing it. But I could not create a collection with this configuration. It gave an error:
ERROR: Error CREATEing SolrCore 'my-search': Unable to create core
[my-search] Caused by: Invalid maxEdits
Max 2 Edits seems to be a serious limitation. I wonder what is the use of passing the fractional value after the ~ operator.
My Usecase:
I have a contact database. I am supposed to detect the duplicates based on three parameters : Name, Email and Phone. So I rely on Solr for Fuzzy search. Email and Phone are relatively easy to work with simple assumptions. Name seems to be a bit tricky. For each word in the Name, I plan to do a fuzzy search. I expected the optional parameter after ~ to work without the maxEdit distance limitation.
The documentation no longer suggests using a fractional value after the tilde - see http://lucene.apache.org/core/4_6_0/queryparser/org/apache/lucene/queryparser/classic/package-summary.html#Fuzzy_Searches for more information.
However, you are correct that only 2 changes are allowed to be made to the search string in order to carry out a fuzzy search. I would guess this limitation strikes a balance between efficiency and usefulness.
The maxEdits parameter in solrconfig.xml applies to the DirectSpellChecker configuration, and doesn't affect your searching, unless you're using the spell checker.
For your use case, your best approach may be to index the name field twice, using different field configurations: one using a simple set of analyzers and filters (ie. StandardTokenizerFactory, StandardFilterFactory, LowerCaseFilterFactory), and the other using a phonetic matcher such as the Beider-Morse filter. You can use the first field to carry out fuzzy searches, and the second version to look for names which may be spelled differently but sound the same as the name being checked.
Hi
I have a very specific need in my company for the system's search engine, and I can't seem to find a solution.
We have a SOLR index of items, all of them have the same fields, with one of the fields being "Type", (And ofcourse, "Title", "Text", and so on).
What I need is: I get an Item Type and a Query String, and I need to return a list of search suggestion with each also saying how meny items of the correct type will that suggested string return.
Something like, if the original string is "goo" I'll get
Goo 10
Google 52
Goolag 2
and so on.
now, How do I do it?
I don't want to re-query SOLR for each different suggestion, but if there is no other way, I just might.
Thanks in advance
you can try edge n-gram tokenization
http://search.lucidimagination.com/search/document/CDRG_ch05_5.5.6
You can try facets. Take a look at my more detailed description ('Autocompletion').
This was implemented at http://jetwick.com with Solr ... now using ElasticSearch but the Solr sources are still available and the idea is also the identical https://github.com/karussell/Jetwick
The SpellCheckComponent of Solr (that gives the suggestions) have extended results that can give the frequency of every suggestion in the index - http://wiki.apache.org/solr/SpellCheckComponent#Extended_Results.
However, the .Net component SolrNet, does not currently seem to support the extendedResults option: "All of the SpellCheckComponent parameters are supported, except for the extendedResults option" - http://code.google.com/p/solrnet/wiki/SpellChecking.
This is implemented using a facet field query with a Prefix set. You can test this using the xml handler like this:
http://localhost:8983/solr/select/?rows=0&facet=true&facet.field=type&f.type.prefix=goo