[WEB4LIB] RE: Decision tree for Web resources

[Roy Tennant]

The fact that I was also thinking of exactly the scenario you described 
(down to even the tool you mentioned) is deeply gratifying. At least I 
know if I'm nuts, I have company.  I continue to think that such a 
strategy might prove the most fruitful, but as you identified, the 
issue is getting enough "fodder" to work with. I'm wondering if 
downloading large numbers of citations and/or full-text articles might 
work. Given the fact that no one would see the citations, and the 
entire purpose is to be able to guide someone to the database from 
which they came seems to justify such a procedure. It certainly seems 
worth a try.
Roy

On Mar 16, 2005, at 1:26 PM, Tito Sierra wrote:

> Roy, since you asked for ideas on this...
>
> One strategy (which may or may not yield fruit in your case) is to 
> create a local index of descriptions and/or keywords associated with 
> your subject-specific databases, and run a search against this to 
> construct your short list of subject specific databases to include in 
> your metasearch.  I'm thinking here of a tool such as SWISH-E that can 
> create an inverted index of a pile of text or XML files, each file 
> containing keyword fodder for a specific database.  As part of your 
> search pre-processing algorithm you can run an "AND" search of the 
> user query against this locally stored index and see if you generate a 
> signal for any of the subject-specific databases.  If you do, grab the 
> top three most relevant subject-specific database identifiers and 
> include them in your metasearch pipeline.
>
> Of course, this strategy presumes you have keyword-rich database 
> descriptions to work from which may not be the case.  There are ways 
> of generating keyword fodder for stuff like this, perhaps by indexing 
> the names of included journal titles or something similar.  You can 
> update the index for this sort of thing on an as needed basis, or on a 
> regular basis if your keyword fodder is evolving.  One benefit of this 
> strategy is that could be done with a low performance impact to the 
> user since the performance hit for running a keyword search on a 
> locally stored inverted index will likely be unnoticeable to the user.
>
> Tito Sierra
> Digital Library Initiatives
> North Carolina State University
>
> On Mar 16, 2005, at 12:54 PM, Roy Tennant wrote:
>>
>> In other words, a search is entered, we search it in several large,
>> general purpose databases, but simultaneously also use that query to
>> try to determine which (probably top three) subject-focused databases
>> would apply for that search, and display those to the user as well
>> along with the search results from the general databases. We haven't
>> yet figured out the best way of doing that database advisor function,
>> which is why we are very interested in the work or Ross and others who
>> are trying different methods. If anyone has any great ideas, I'm all
>> ears! Thanks,
>> Roy
>
>