Ethan, kind thanks, and three questions to you (and I presume UVirginiašs
Solr refers to Blacklight, thus am CC-ing Vufind-ers):
1. I asked myself if WorldCat indexes and upkeeps FAST, why do you need to
index FAST in your local Solr?š, and I answered: because you want to link
FAST to your local bibs. Is this the case?
2. If it is the case, are you going to load FAST on a weekly basis, cronjob
the procedure?
3. If you are, what do you need FAST autusoggester for?
Yašaqov
On 12/10/09 4:35 PM, "Ethan Gruber" <[log in to unmask]> wrote:
> Nice work, Ralph. That's really slick. I have all the subject terms in the
> solr index, but I would like to eventually integrate the Worldcat data to
> make the results more relevant (rather than just sorted alphabetically since
> each subject occurs only once).
>
> I have yet to adapt my Orbeon forms to handle dynamic querying of the terms
> in Solr, but would like to have that done in the next week or two (I hope!).
>
> Here's a sample of the data:
>
> http://beta.scholarslab.org:9080/solr-1.4/terms?terms.fl=subject&terms.limit=2
> 5&terms.prefix=Egy
>
> The terms.prefix parameter displays terms that start with the letters
> inputted. It's extremely fast, so I have no doubt I can use it for
> autosuggest per keystroke.
>
> Ethan
>
> On Thu, Dec 10, 2009 at 4:07 PM, LeVan,Ralph <[log in to unmask]> wrote:
>
>> > In a rare demonstration of doing as promised, I have a FAST
>> > AutoSuggester running based on that data. An HTML demonstration of the
>> > service can be found at http://orlabs.oclc.org/FAST/autosuggest.html and
>> > the underlying AutoSuggester is running at
>> > http://orlabs.oclc.org/FAST/AutoSuggest. Searches from the HTML go to
>> > WorldCat.
>> >
>> > An example of a suggestion request would be
>> > http://orlabs.oclc.org/FAST/AutoSuggest?query=0
>> >
>> > It returns JSON, which the above HTML link demonstrates the use of.
>> >
>> > My AutoSuggester is just a thin interface to an SRU database. The query
>> > that comes to the AutoSuggester is turned into an SRU query and the
>> > resulting record is dropped into the AutoSuggester response. The link
>> > to the SRU database for the above query for "0" would be
>> > http://orlabs.oclc.org/identities/search/AutoSuggestFAST?query=fragment+
>> >
>> exact+%220%22<http://orlabs.oclc.org/identities/search/AutoSuggestFAST?query=
>> fragment+%0Aexact+%220%22>
>> >
>> > I've put up a file containing all the records I loaded into my database.
>> > The records contain 2 tab delimited fields. The first field is the key
>> > to the record and corresponds to the user's keystrokes (e.g. '0' above).
>> > The second field contains the JSON response which is an ordered array of
>> > terms. I load that into the moral equivalent of Lucene and you see the
>> > results in that SRU search. The file can be found at
>> > http://orlabs.oclc.org/FAST/AutoSuggestFAST.zip
>> >
>> > Let me know if you have any problems or questions.
>> >
>> > Ralph
>> >
>> >
>>> > > -----Original Message-----
>>> > > From: LeVan,Ralph
>>> > > Sent: Thursday, December 10, 2009 11:12 AM
>>> > > To: [log in to unmask]
>>> > > Subject: RE: [CODE4LIB] Auto-suggest and the id.loc.gov LCSH web
>> > service
>>> > >
>>> > > We've made some progress on this topic.
>>> > >
>>> > > I have available a list of our FAST subject headings. They are
>> > derived from
>>> > > LCSH and may be of some use. The folks that produced this file are
>> > working on
>>> > > producing a similar file for LCSH.
>>> > >
>>> > > The file can be found at http://orlabs.oclc.org/FAST/fastOutput.zip.
>>> > >
>>> > > The file contains tab delimited records. The first column is the ID
>> > number of the
>>> > > FAST record that the term comes from. The second column is the MARC
>>> > > Authorities field that the term came from. The third column is the
>> > term itself. The
>>> > > 4th column is the count of records in WorldCat that are retrieved when
>> > that term
>>> > > is used in the Keyword index. The 5th column is the count of records
>> > in
>>> > > WorldCat that are retrieved when that term is used in the Subject
>> > index.
>>> > >
>>> > > I expect to have an AutoSuggester built on this today.
>>> > >
>>> > > Ralph
>> >
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