It is definitely going to increase the index size, but not any more than than the external one would (if my understanding is correct).

The nice thing is that you don't have to try and keep documents numbers in sync - it will be automatic.

Maybe I don't understand what your external index is storing. Given that the document contains 'robert' but the user enters' obert', what is the process to find the matching documents?

Is the external index essentially a constant list, that given obert, the source words COULD BE robert, tobert, reobert etc., and it contains no document information so:

given the source word X, and an edit distance k, you ask the external dictionary for possible indexed words, and it returns the list, and then use search lucene using each of those words?

If the above is the case, it certainly seems you could generate this list in real-time rather efficiently with no IO (unless the external index only stores words which HAVE BEEN indexed).

I think the confusion may be because I understand Otis's comments, but they don't seem to match what you are stating.

Essentially performing any term match requires efficient searching/ matching of the term index. If this is efficient enough, I don't think either process is needed - just an improved real-time fuzzy possibilities word generator.

On Jan 6, 2009, at 3:58 PM, Robert Muir wrote:

i see, your idea would definitely simplify some things.

What about the index size difference between this approach and using separate index? Would this separate field increase index size?

I guess my line of thinking is if you have 10 docs with robert, with separate index you just have robert, and its deletion neighborhood one time. with this approach you have the same thing, but at least you must have document numbers and the other inverted index stuff with each neighborhood term. would this be a significant change to size and/or performance? and since the documents have multiple terms there is additional positional information for slop factor for each neighborhood term...

i think its worth investigating, maybe performance would actually be better, just curious. i think i boxed myself in to auxiliary index because of some other irrelevant thigns i am doing.

On Tue, Jan 6, 2009 at 4:42 PM, robert engels <reng...@ix.netcom.com> wrote: I don't think that is the case. You will have single deletion neighborhood. The number of unique terms in the field is going to be the union of the deletion dictionaries of each source term.

For example, given the following documents A which have field 'X' with value best, and document B with value jest (and k == 1).

A will generate est bst, bet, bes, B will generate est, jest, jst, jes

so field FieldXFuzzy contains (est:AB,bst:A,bet:A,bes:A,jest:B,jst:B,jes)

I don't think the storage requirement is any greater doing it this way.


3.2.1 Indexing
For all words in a dictionary, and a given number of edit operations k, FastSS generates all variant spellings recursively and save them as tuples of type vā€² āˆˆ Ud (v, k) ā†’ (v, x) where v is a dictionary word and x a list of deletion
positions.

Theorem 5. Index uses O(nmk+1) space, as it stores al l the variants for n
dictionary words of length m with k mismatches.


3.2.2 Retrieval
For a query p and edit distance k, first generate the neighborhood Ud (p, k).
Then compare the words in the neighborhood with the index, and find
matching candidates. Compare deletion positions for each candidate with
the deletion positions in U(p, k), using Theorem 4.





--
Robert Muir
rcm...@gmail.com

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