To Vishal: My idea is similar to yours. I like to use hash table as
well. But I wonder which hash function can you use to insert and find
keywords with O(1) time? Keywords are not single characters. They are
normal words. That's basically what I am aftering.

On Sep 25, 2:11 pm, Mayur <[EMAIL PROTECTED]> wrote:
> Another possibility is to first pre-process the keywords into
> automaton-like structure (Google for Aho Corasick string matcher), and
> then use it over the document. This would probably be helpful only if
> the number of keywords is much smaller than the document itself..
>
> On 9/25/07, daizisheng <[EMAIL PROTECTED]> wrote:
>
>
>
> > Vishal 写道:
> > > Hash table should give you O(1) insertion and search complexity; which
> > > is what we need, right?
> > > There is no constraint on space complexity, I believe.
>
> > > On 9/24/07, * daizisheng* <[EMAIL PROTECTED]
> > > <mailto:[EMAIL PROTECTED]>> wrote:
>
> > >     the problem is you need a hash table to maintain all the keywords,:)
> > >     because they do not have to be a single characters, or you can
> > >     store them in
> > >     array, but then you need binary search,:)
>
> > >     Vishal 写道:
> > >     > How about keeping two pointers - startp and endp.
> > >     > Keep a count of frequencies of keywords between startp and endp,
> > >     both
> > >     > inclusive. We can use an array / hash table for this.
> > >     > Now, the minimum length substring has to start with a keyword
> > >     and has
> > >     > to end with a keyword.
>
> > >     > 1. Initially startp=0 and endp=1. L = infinity
> > >     > 2. Increment endp till you encounter a keyword or it exceeds the
> > >     total
> > >     > length. Update frequencies. Check if you have all the keywords.
> > >     (This
> > >     > can be done in O(1) using a bitmap or similar). If it exceeds the
> > >     > total length, QUIT.
> > >     > 3. If the str(startp,endp) contains all keywords and length < L,
> > >     save
> > >     > values of startp and endp.
> > >     > 4. Now, increment startp, till you get a keyword. If the
> > >     > str(startp,endp) still contains all keywords, update saved values of
> > >     > startp and endp.
> > >     > 5. Repeat step 4 till str(startp,endp) does NOT contain all
> > >     keywords.
> > >     > 6. Goto step 2.
>
> > >     > The final values of startp and endp should give you the minimum
> > >     summary.
> > >     > Since both values go from 0 to N-1, its O(N).
>
> > >     > ~Vishal
>
> > >     > On 9/24/07, *daizisheng* < [EMAIL PROTECTED]
> > >     <mailto:[EMAIL PROTECTED]>
> > >     > <mailto:[EMAIL PROTECTED] <mailto:[EMAIL PROTECTED]>>> wrote:
>
> > >     >     I think hash method is ok, at lease in expectation way it's
> > >     O(n)
> > >     >     why not use it? it's very effeciently
>
> > >     >     I think there should be some worst case O(n) algorithm, but
> > >     it will be
> > >     >     more complex and not as effecient as the above one in practise
>
> > >     >     Sticker 写道:
> > >     >     > Declare: this question is originally from Google. The
> > >     original form
> > >     >     > is: given a document, how to find a shortest summary
> > >     containing all
> > >     >     > the key words. After translated, it will be: given a
> > >     sequence,
> > >     >     how to
> > >     >     > find a shortest substring that contains all the items
> > >     required.
> > >     >     > Example: a sequence "abaccdefgacel" and a set of key words
> > >     "a", "c",
> > >     >     > "d" and "e". The shortest substring contianing all of the key
> > >     >     words is
> > >     >     > "accde". Find one of such shortest substrings. In the original
> > >     >     > question, there is time complexity boundary O(N), where N
> > >     is the
> > >     >     > length of the sequence.
>
> > >     >     > To me, this problem is rather questionable. So far my solution
> > >     >     > requires a hash table that gives no conflict and can locate a
> > >     >     key word
> > >     >     > in O(1) time. Otherwise the time complexity will
> > >     definitely be
> > >     >     related
> > >     >     > to the number of key words.
>
> > >     >     > Does anyone have idea for a O(N) algorithm to solve this
> > >     problem?
>
> > yes, that's we need. but seems the starter of this thread who did not
> > like hash,:)


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