I work for an organization that has a serious data quality problem with names. There are fifteen databases that contain information about people. For example:
Database 1
Name=Fre&d Blo-ggs DOB 01/01/1980
Database 2
Name=Freddy Bloggs DOB 01/01/1980
If a user searches for Fred Bloggs using my search tool then I want both records to be found. I was thinking about something like this:
SELECT * FROM Person WHERE Soundex('Fred Bloggs') = Soundex('Fre&d Blo-ggs')
Is it advisable to use Soundex like this rather than using replace statements like this:
select Replace(Replace(Replace(Name,',',''),'&',''),'#') from Person
where Replace(Replace(Replace(Name,',',''),'&',''),'#') = #Name
#Name is the variable passed in. Is there a better way of doing it e.g. using regular expressions? Does Soundex affect performance.
Nice idea. I would not suggest using it though. I suppose that "John Right" is not the same as "John Write", even though they hear the same. I mean that in the end, what it matters is what you want to compare.... If you want to compare if the name sounds are the same, then SOUNDEX is fine.
However, I would suggest correcting your data somehow. This would be a real solution, although I can imagine that is not an easy one.
Hope I helped!
If soundex is better than regex depends of your data. For example there are different soundex versions for different languages. You have to check with your data, which is better..
Of course soundex does affect performance as any other additional functions you are calling. If performance becomes a problem, I would advise to add an additional column with the already computed soundex or normalized names and to create an index over it.
From own experience I think a normalized / simplified search criterion as e.g. parts of surname, prename and month of birth date should be sufficient to get all persons, but not too many, so a user can decide which person (s)he really wants to choose.
Soundex wont help you. you will stuck if a consonant appears in the name by mistake.
Its better you go for string distance and specify a percentage. A kind of fuzzy matching.
Have a look at the below link for fuzzy matching using levenshtein edit distance algorithm.
Levenshtein edit distance - MS SQL SERVER
Related
I have a function that uses the SQL DIFFERENCE function to see if the name of a client is similar to a client already in the database
SELECT ID FROM People p
WHERE DIFFERENCE(p.FullName, #fullName) = 4
Being #fullname a variable passed to the function. The issue I'm having is that if I pass "pedro sanchez" as a parameter, the query will bring me all the Peter's in the database, or if I enter "pablo sanchez", it'll bring record "PEOPLE'S CREDIT UNION".
As I understand the DIFFERENCE function should returns 4 when the two strings are almost identical, but the results I'm having say otherwise.
Is there a way to further specify the resemblance to the DIFFERENCE function, or maybe another approach in finding similar names ?
Difference() is based on soundex(), which in turn -- to be frank -- is a lousy system for comparing strings. Let me add a caveat: it is pretty good for the purpose it was designed for, which is matching last names of people in English. You can read about the rules here and you can try it out here. Using the latter link, you can see that "Pedro" and "People" have the same code, P-140.
Soundex encodes the consonants and basically the first four matching consonants the list it cares about. (Some languages, such as Hawaiian and other Polynesian languages are rather light in consonants. One assumes the designers were not thinking about names in such languages.)
When you are looking for proximity among written strings, Levenshtein distance is a common metric. Unfortunately, SQL Server does not have this functionality built-in, but you can easily find implementations on the web. For most real applications, Levenshtein distance is too slow. Happily, the functionality of the full text search component is usually sufficient for most purposes.
I have a SQL server table which contains several string columns. I need to write an application which gets a string and search for similar strings in SQL server table.
For example, if I give the "مختار" or "مختر" as input string, I should get these from SQL table:
1 - مختاری
2 - شهاب مختاری
3 - شهاب الدین مختاری
I've searched the net for a solution but I have found nothing useful. I've read this question , but this will not help me because:
I am using MS SQL Server not MySQL
my table contents are in Persian, so I can't use Levenshtein distance and similar methods
I prefer an SQL Server only solution, not an indexing or daemon based solution.
The best solution would be a solution which help us sort result by similarity, but, its optional.
Do you have any suggestion for that?
Thanks
MSSQL supports LIKE which seems like it should work. Is there a reason it's not suitable for your program?
SELECT * FROM table WHERE input LIKE '%مختار%'
Hmm.. considering that you read the other post you probably know about the like operator already... maybe your problem is "getting the string and searching for something similar"?
--This part searches for a string you want
declare #MyString varchar(max)
set #MyString = (Select column from table
where **LOGIC TO FIND THE STRING GOES HERE**)
--This part searches for that string
select searchColumn, ABS(Len(searchColumn) - Len(#MyString)) as Similarity
from table where data LIKE '%' + #MyString + '%'
Order by Similarity, searchColumn
The similarity part is something like the thing you posted. If the strings are "more similar" meaning that they have a similar length, they will be higher on the results query.
The absolute part can be avoided obviously but I did it just in case.
Hope that helps =-)
Besides like operator, you can use the condition WHERE instr(columnname, search) > 0; however this is generally slower. What it does is return the starting position of a string within another string. thus if searching in ABCDEFG for CD it would return 3. 3>0, so the record would be returned. However in the case you've described, like seems to be the best solution.
The general problem is that in languages where the same letter has different writing form in the beginning, middle and at the end of word, and thus - different codes - we can try to use specific Persian collations, but in general this will not help.
The second option - is to use SQL FTS abilities, but again - if it has not special language module for the language - it is much less useful.
And most general way - to use your own language processing - which is very complex task at all. The next keywords and google can help to understand the size of the problem: DLP, words and terms, bi-gramms, n-gramms, grammar and morphology inflection
Try to use the Built-in Soundex() And Difference() functions. I hope they work fine for Persian.
Look at the following reference:
http://blog.hoegaerden.be/2011/02/05/finding-similar-strings-with-fuzzy-logic-functions-built-into-mds/
Similarity() function helps you to sort result by similarity (as you asked in your question) and it is also possible using algorithms different from Levenshtein edit distance depends on the Value for #method Algorithm:
0 The Levenshtein edit distance algorithm
1 The Jaccard similarity coefficient algorithm
2 A form of the Jaro-Winkler distance algorithm
3 Longest common subsequence algorithm
Like operator may not do what he is asking for. Like for example, if i have a record value "please , i want to ask a question' in my database record. and lets say on my query, i want to find a match similarity like this 'Can i ask a question, please'. like operator may do this using like %[your senttence] or [your sentence]% but it is not advisable to use it for string similarity cos sentences may change and all your like logic may not fetch the matching records. It is advisable to use naive bayes text classification for similarities assigning labels to your sentences or you can try the semantic search function in MSSQL server
Given your data stored somewhere in a database:
Hello my name is Tom I like dinosaurs to talk about SQL.
SQL is amazing. I really like SQL.
We want to implement a site search, allowing visitors to enter terms and return relating records. A user might search for:
Dinosaurs
And the SQL:
WHERE articleBody LIKE '%Dinosaurs%'
Copes fine with returning the correct set of records.
How would we cope however, if a user mispells dinosaurs? IE:
Dinosores
(Poor sore dino). How can we search allowing for error in spelling? We can associate common misspellings we see in search with the correct spelling, and then search on the original terms + corrected term, but this is time consuming to maintain.
Any way programatically?
Edit
Appears SOUNDEX could help, but can anyone give me an example using soundex where entering the search term:
Dinosores wrocks
returns records instead of doing:
WHERE articleBody LIKE '%Dinosaurs%' OR articleBody LIKE '%Wrocks%'
which would return squadoosh?
If you're using SQL Server, have a look at SOUNDEX.
For your example:
select SOUNDEX('Dinosaurs'), SOUNDEX('Dinosores')
Returns identical values (D526) .
You can also use DIFFERENCE function (on same link as soundex) that will compare levels of similarity (4 being the most similar, 0 being the least).
SELECT DIFFERENCE('Dinosaurs', 'Dinosores'); --returns 4
Edit:
After hunting around a bit for a multi-text option, it seems that this isn't all that easy. I would refer you to the link on the Fuzzt Logic answer provided by #Neil Knight (+1 to that, for me!).
This stackoverflow article also details possible sources for implentations for Fuzzy Logic in TSQL. Once respondant also outlined Full text Indexing as a potential that you might want to investigate.
Perhaps your RDBMS has a SOUNDEX function? You didn't mention which one was involved here.
SQL Server's SOUNDEX
Just to throw an alternative out there. If SSIS is an option, then you can use Fuzzy Lookup.
SSIS Fuzzy Lookup
I'm not sure if introducing a separate "search engine" is possible, but if you look at products like the Google search appliance or Autonomy, these products can index a SQL database and provide more searching options - for example, handling misspellings as well as synonyms, search results weighting, alternative search recommendations, etc.
Also, SQL Server's full-text search feature can be configured to use a thesaurus, which might help:
http://msdn.microsoft.com/en-us/library/ms142491.aspx
Here is another SO question from someone setting up a thesaurus to handle common misspellings:
FORMSOF Thesaurus in SQL Server
Short answer, there is nothing built in to most SQL engines that can do dictionary-based correction of "fat fingers". SoundEx does work as a tool to find words that would sound alike and thus correct for phonetic misspellings, but if the user typed in "Dinosars" missing the final U, or truly "fat-fingered" it and entered "Dinosayrs", SoundEx would not return an exact match.
Sounds like you want something on the level of Google Search's "Did you mean __?" feature. I can tell you that is not as simple as it looks. At a 10,000-foot level, the search engine would look at each of those keywords and see if it's in a "dictionary" of known "good" search terms. If it isn't, it uses an algorithm much like a spell-checker suggestion to find the dictionary word that is the closest match (requires the fewest letter substitutions, additions, deletions and transpositions to turn the given word into the dictionary word). This will require some heavy procedural code, either in a stored proc or CLR Db function in your database, or in your business logic layer.
You can also try the SubString(), to eliminate the first 3 or so characters . Below is an example of how that can be achieved
SELECT Fname, Lname
FROM Table1 ,Table2
WHERE substr(Table1.Fname, 1,3) || substr(Table1.Lname,1 ,3) = substr(Table2.Fname, 1,3) || substr(Table2.Lname, 1 , 3))
ORDER BY Table1.Fname;
I want to show the closest related item for a product. So say I am showing a product and the style number is SG-sfs35s. Is there a way to select whatever product's style number is closest to that?
Thanks.
EDIT: to answer your questions. Well I definitely want to keep the first 2 letters as that is the manufacturer code but as for the part after the first dash, just whatever matches closest. so for example SG-sfs35s would match SG-shs35s much more than SG-sht64s. I hope this makes sense whenever I do LIKE product_style_number it only pulls the exact match.
There normally isn't a simple way to match product codes that are roughly similar.
A more SQL friendly solution is to create a new table that maps each product to all the products it is similar to.
This table would either need to be maintained manually, or a more sophisticated script can be executed periodically to update it.
If your product codes follow a consistent pattern (all the letters are the same for similar products, with only the numbers changing), then you should be able to use a regular expression to match the similar items. There are docs on this here...
It sounds like what you want is levenshtein distance .
Unfortunately, there isn't a built-in levenshtein function for mysql, but some folks have come up with a user-defined function that does it(deadlink).
You will probably want to do it as a stored procedure, as I expect that the algorithm may not be trivial.
For example, you may split the term at the -, so you have two parts. You do a LIKE query on each part and use that to make a decision.
You could just loop though, replacing the last character with "%" until you get at least one result, in your stored procedure.
Sounds like you need something like Lucene, though i'm not sure if that would be overkill for your situation. But it certainly would be able to do text searches and return the ones most similar first.
If you need something more simple I would try to start by searching with the full product code, then if that doesn't work try to use wildcards/remove some characters until you return a result.
JD Isaacks.
This situation of yours is very simple to solve.
It`s not like you need to use Artificial Intelligence like the Google.
http://www.w3schools.com/sql/sql_wildcards.asp
Take a look at this manual at w3schools about wildcards to use with your SELECT code.
But also you will need to create a new table with 3 columns: LeftCode, RightCode and WildCard.
Example:
Rows on Table:
LeftCode = SG | RightCode = 35s | WildCard = SG-s_s35s
LeftCode = SG | RightCode = 64s | WildCard = SG-s_t64s
SQL Code
If the user typed the code that matches the row1 of the table:
SELECT * FROM PRODUCTS WHERE CODE LIKE "$WildCard";
Where $WildCard is the PHP variable containing the column 3 of the new table.
I hope I helped, even 4 years late...
I am trying to determine what the best way is to find variations of a first name in a database. For example, I search for Bill Smith. I would like it return "Bill Smith", obviously, but I would also like it to return "William Smith", or "Billy Smith", or even "Willy Smith". My initial thought was to build a first name hierarchy, but I do not know where I could obtain such data, if it even exists.
Since users can search the directory, I thought this would be a key feature. For example, people I went to school with called me Joe, but I always go by Joseph now. So, I was looking at doing a phonetic search on the last name, either with NYSIIS or Double Metaphone and then searching on the first name using this name heirarchy. Is there a better way to do this - maybe some sort of graded relevance using a full text search on the full name instead of a two part search on the first and last name? Part of me thinks that if I stored a name as a single value instead of multiple values, it might facilitate more search options at the expense of being able to address a user by the first name.
As far as platform, I am using SQL Server 2005 - however, I don't have a problem shifting some of the matching into the code; for example, pre-seeding the phonetic keys for a user, since they wouldn't change.
Any thoughts or guidance would be appreciated. Countless searches have pretty much turned up empty. Thanks!
Edit: It seems that there are two very distinct camps on the functionality and I am definitely sitting in the middle right now. I could see the argument of a full-text search - most likely done with a lack of data normalization, and a multi-part approach that uses different criteria for different parts of the name.
The problem ultimately comes down to user intent. The Bill / William example is a good one, because it shows the mutation of a first name based upon the formality of the usage. I think that building a name hierarchy is the more accurate (and extensible) solution, but is going to be far more complex. The fuzzy search approach is easier to implement at the expense of accuracy. Is this a fair comparison?
Resolution: Upon doing some tests, I have determined to go with an approach where the initial registration will take a full name and I will split it out into multiple fields (forename, surname, middle, suffix, etc.). Since I am sure that it won't be perfect, I will allow the user to edit the "parts", including adding a maiden or alternate name. As far as searching goes, with either solution I am going to need to maintain what variations exists, either in a database table, or as a thesaurus. Neither have an advantage over the other in this case. I think it is going to come down to performance, and I will have to actually run some benchmarks to determine which is best. Thank you, everyone, for your input!
In my opinion you should either do a feature right and make it complete, or you should leave it off to avoid building a half-assed intelligence into a computer program that still gets it wrong most of the time ("Looks like you're writing a letter", anyone?).
In case of human names, a computer will get it wrong most of the time, doing it right and complete is impossible, IMHO. Maybe you can hack something that does the most common English names. But actually, the intelligence to look for both "Bill" and "William" is built into almost any English speaking person - I would leave it to them to connect the dots.
The term you are looking for is Hypocorism:
http://en.wikipedia.org/wiki/Hypocorism
And Wikipedia lists many of them. You could bang out some Python or Perl to scrape that page and put it in a db.
I would go with a structure like this:
create table given_names (
id int primary key,
name text not null unique
);
create table hypocorisms (
id int references given_names(id),
name text not null,
primary key (id, name)
);
insert into given_names values (1, 'William');
insert into hypocorisms values (1, 'Bill');
insert into hypocorisms values (1, 'Billy');
Then you could write a function/sproc to normalize a name:
normalize_given_name('Bill'); --returns William
One issue you will face is that different names can have the same hypocorism (Albert -> Al, Alan -> Al)
I think your basic approach is solid. I don't think fulltext is going to help you. For seeding, behindthename.com seems to have large amount of the data you want.
Are you using SQl Server 2005 Express with Advanced Services as to me it sounds you would benefit from the Full Text indexing and more specifically Contains and Containstable which you can use with specific instructions here is a link for the uses of Containstable:
http://msdn.microsoft.com/en-us/library/ms189760.aspx
and here is the download link for SQL Server 2005 With Advanced Services:
http://www.microsoft.com/downloads/details.aspx?familyid=4C6BA9FD-319A-4887-BC75-3B02B5E48A40&displaylang=en
Hope this helps,
Andrew
You can use the SQL Server Full Text Search and do an inflectional search.
Basically like:
SELECT ProductId, ProductName
FROM ProductModel
WHERE CONTAINS(CatalogDescription, ' FORMSOF(THESAURUS, metal) ')
Check out:
http://en.wikipedia.org/wiki/SQL_Server_Full_Text_Search#Inflectional_Searches
http://msdn.microsoft.com/en-us/library/ms345119.aspx
http://www.mssqltips.com/tip.asp?tip=1491
Not sure what your application is, but if your users know at the time of sign up that people from their past might be searching the database for them, you could offer them the chance in the user profile to define other names they might be known as (including last names, women change these all the time and makes finding them much harder!) and that they want people to be able to search on. Store these in a separate related table. Then search on that. Just make the structure such that you can define one name as the main name (the one you use for everything except the search.)
You'll find that you're dabbling in an area known as "Natural Language Processing" and you'll need to do several things, most of which can be found under the topic of stemming.
Simplistic stemming simply breaks the word apart, but more advanced algorithms associate words that mean the same thing - for instance Google might use stemming to convert "cat" and "kitten" to "feline" and search for all three, weighing the actual word provided by the user as slightly heavier so exact matches return before stemmed matches.
It's a known problem, and there are open source stemmers available.
-Adam
No, Full Text searches will not help to solve your problem.
I think you might want to take a look at some of the following links: (Funny, no one mentioned SoundEx till now)
SoundEx - MSDN
SoundEx - Google results
InformIT - Tolerant Search algorithms
Basically SoundEx allows you to evaluate the level of similarity in similar sounding words. The function is also available on SQL 2005.
As a side issue, instead of returning similar results, it might prove more intuitive to the user to use a AJAX based script to deliver similar sounding names before the user initiates his/her search. That way you can show the user "similar names" or "did you mean..." kind of data.
Here's an idea for automatically finding "name synonyms" like Bill/William. That problem has been studied in the broader context of synonyms in general: inducing them from statistics of which words commonly appear in the same contexts in a large text corpus like the Web. You could try combining that approach with a list of names like Moby Names; I don't know if it's been done before.
Here are some pointers.