On 1/19/06, Mathias Lux <[EMAIL PROTECTED]> wrote:
>
>
> > Actually, my problem is that, for instance, for a document d,
> > Its feature
> > vector may be keywords and concepts. I don't know how to
> > weight the two
> > items. Right now, i used a stupid method, given a document d,
> > i can obtain a
> > rank D based on keyword method. Also, it is annotated with a
> > concept c (The
> > most simple example) . People can have a rank C of these
> > concepts in the
> > domain ontology, where the most relevant concepts should be
> > the at top of
> > this concept list. Finally, document's rank is decided by the
> > sum of (C +
> > D).
>
> hmm, if you index the concepts e.g. based on ist URI in a Lucene Filed
> you can set a boost value at indexing time like this:
>
> Field conceptField = Field.Text("classification",
> "http://concepts.server.com/classification/car/mercedes";)
> conceptField.setBoost(1.3f);
>
> So your concept for this document, where the filed is added, is boosted
> in relevance computation.
>
> if you know the concept boost value at search time you can add the boost
> value to the query:
> e.g. querying for
>
> classification:"http://concepts.server.com/classification/car/mercedes"^
> 4
>
> Of course you have to think about the whole thing, but I think with good
> boost values it would work.
>
> - mathias
>
> ps. instead of C+D I would use (l-1)*C + l*D, so l from [0,1] can be
> used to specify if concept or content has more influence.
I will compute each concepts relevant to each query. Thus, i cannot set the
boost value. Actually, I use the (l-1)*C + l*D method in my prototype. But
my supervisor said this method is funny as it is too simple.
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--
Regards
Jiang Xing
