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Fuzzy search can be used in various applications, for example:
● Fault-tolerant search in text columns (for example, html or pdf): Search for documents on 'Driethanolamyn'
and find all documents that contain the term 'Triethanolamine'.
● Fault-tolerant search in structured database content: Search for a product called 'coffe krisp biscuit' and find
'Toffee Crisp Biscuits'.
● Fault-tolerant check for duplicate records: Before creating a new customer record in a CRM system, search for
similar customer records and verify that there are no duplicates already stored in the system. When, for
example, creating a new record 'SAB Aktiengesellschaft & Co KG Deutschl.' in 'Wahldorf', the system shall
bring up 'SAP Deutschland AG & Co. KG' in 'Walldorf' as a possible duplicate.
You can call the fuzzy search by using the CONTAINS predicate with the FUZZY option in the WHERE clause of a
SELECT statement.
Fuzzy Score
SELECT * FROM
WHERE CONTAINS (, , FUZZY (0.8))
Note: You can improve the performance of a fuzzy search on a text column by defining a fuzzy
index at the column. You can define a fuzzy index with the option FUZZY SEARCH INDEX ON in
the CREATE FULLTEXT INDEX statement or in the definition of data type TEXT.
The fuzzy search algorithm calculates a fuzzy score for each string comparison. The higher the score, the more
similar the strings are. A score of 1.0 means the strings are identical. A score of 0.0 means the strings have
nothing in common.
You can request the score in the SELECT statement by using the SCORE() function. You can sort the results of a
query by score in descending order to get the best records first (the best record is the record that is most similar
to the user input). When a fuzzy search of multiple columns is used in a SELECT statement, the score is returned
as an average of the scores of all columns used.
When searching text columns, a TF/IDF (term frequency/inverse document frequency) score is returned by
default instead of the fuzzy score. The fuzzy score influences the TF/IDF calculation, but it is important to keep in
mind that, with TF/IDF, the range of the score values returned is normed to the interval between 0.0 and 1.0, and
the best record always gets a score of 1.0, regardless of its fuzzy score.
The TF/IDF calculation can be disabled so that you get the fuzzy score instead. In particular, this makes sense for
short-text columns containing data such as product names or company names. On the other hand, you should
use TF/IDF for long-text columns containing data such as product descriptions, HTML data, or Word and PDF
documents.
Option spellCheckFactor
There are two use cases for the option spellCheckFactor.
● A) This option allows you to set the score for terms that are not fully equal but that would be a 100% match
because of the internal character standardization used by the fuzzy search.
For example, the terms 'Café' and 'cafe' give a score of 1.0 although the terms are not equal. For some users it
may be necessary to distinguish between both terms.
SAP HANA Developer Guide
Enabling Search
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