you will have to use the concept of edit distance ..
google for edit distance and you may find too many good articles on it.
"Levenshtein distance" is one such algorithm for measuring the amount of
difference between two sequences [edit distance]
On Mon, Sep 13, 2010 at 2:55 PM, Praveen Baskar <praveen200...@gmail.com>wrote:
> i think that we have to generate substrings from the given string such that
> the similarity is above 50%
> for eg.
> word ="foo"
> we have to generate the strings which must be greater than half of the
> given string length
> {"fo","oo"} (in this case)
>
> after this operation we have the following string set {"foo","fo","oo"}
>
> then we can do select* from product where name like '%foo%'....select*
> from product where name like '%fo%'..... select* from product where name
> like '%oo%'
>
>
> please do correct me if i am wrong
> On Mon, Sep 13, 2010 at 1:01 PM, SVIX <saivivekh.swaminat...@gmail.com>wrote:
>
>> select * from product
>> where
>> name like '%foo%'
>> and len(name) <=6;
>>
>> btw, how do u define similarity? i'm guessing it wouldn't be this
>> simple...
>>
>> On Sep 12, 5:12 am, Snoopy Me <thesnoop...@gmail.com> wrote:
>> > You are given the amazon.com database which consists of names of
>> > millions of products. When a user enters a search query for particular
>> > object with the keyword say "foo" , output all the products which have
>> > names having 50% or more similarity with the given keyword ie "foo"
>> >
>> > Write the most efficient algorithm for the same.
>>
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>
>
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regards ,
Anuj Maurice
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