i think edit distance algorithm can not be used here because in edit
distance problem we have a target string and a source string. Here we dont
have any target word.
I think trie can be used with some preprocessing.

On Thu, Nov 24, 2011 at 11:59 PM, atul anand <[email protected]>wrote:

> http://blog.notdot.net/2007/4/Damn-Cool-Algorithms-Part-1-BK-Trees
>
> this would help.
>
>
> On Thu, Nov 24, 2011 at 9:49 PM, Vijay Meena <[email protected]> wrote:
>
>> Can you please elaborate...
>>
>>
>> On Thu, Nov 24, 2011 at 12:14 AM, atul anand <[email protected]>wrote:
>>
>>>
>>> yes levenshtein distance and BK tree can be used to solve this.
>>> where edge weight between nodes is equal to levenshtein distance.
>>>
>>>
>>> On Wed, Nov 23, 2011 at 7:14 PM, abhishek kumar 
>>> <[email protected]>wrote:
>>>
>>>> You are given a word and a dictionary. Now propose an algorithm edit
>>>> the word (insert / delete characters) minimally to get a word that
>>>> also exists in the dictionary. Cost of insertion and deletion is same.
>>>> Write pseudocode for it.
>>>>
>>>> Seems like minimum edit distance problem but some modification is
>>>> needed.
>>>>
>>>>
>>>> --
>>>> Abhishek Kumar
>>>> B.Tech(IT) Graduate
>>>> Allahabad
>>>> Contact no-+919663082731
>>>>
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