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 >> >