Lucene's scalability is not in question. The simple solution of
rebuilding the string of terms is what I referred to as not being
scalable. For instance, consider the following term vector:
termFreqVector (freq {myTermField: red/69, green/79, blue/899})
Recreating a string with 69
Adding new terms and re-indexing the document is the desired behavior.
One (non-scalable) solution would be to parse the toString of the
termFreqVector (freq {myTermField: red/2, green/1, blue/1}) and create a
new string representation of the expanded terms: (red red green blue)
This obviously
How would one go about adding additional terms to a field which is not
stored literally, but instead has a termFreqVector? For example:
If DocumentA was indexed originally with:
myTermField: red green blue
termFreqVector would look like:
freq {myTermField: red/1, green/1, blue/1}
Now,
gs)"
>
> You can play with MultiFieldQueryParser a bit.
>
> regards,
> Volodymyr Bychkoviak
>
> Ryan Skow wrote:
>
>>Here is the logical structure of the document I'm working with:
>> The 'Document' has two fields:
>>'includes'
Here is the logical structure of the document I'm working with:
The 'Document' has two fields:
'includes' - List of terms that provide positive boost
'excludes' - List of terms that provide negative boost
Here is a usage scenario:
DocumentA
includes: red green blue
exclud
