Hi Dan,
You might want to take a look at pazpar2 [1], an open-source, federated
search engine with first-class support for SOLR (with addition to standard
information retrieval protocols like Z39.50/SRU).
[1] http://www.indexdata.com/pazpar2
On Thu, Sep 5, 2013 at 9:55 PM, Paul Libbrecht wrote
Hello list,
A student of a friend of mine made his masters on that topic, especially about
federated ranking.
I have copied his text here:
http://direct.hoplahup.net/tmp/FederatedRanking-Koblischke-2009.pdf
Feel free to contact me to contact Robert Koblischke for questions.
Pa
On Mon, Aug 26, 2013 at 9:06 PM, Amit Jha wrote:
> Would you like to create something like
> http://knimbus.com
>
I work at the National Library of Medicine. We are moving our library
catalog to a newer platform, and we will probably include articles. The
article's content and meta-data are
On Tue, Aug 27, 2013 at 3:33 AM, Bernd Fehling <
bernd.fehl...@uni-bielefeld.de> wrote:
> Years ago when "Federated Search" was a buzzword we did some development
> and
> testing with Lucene, FAST Search, Google and several other Search Engines
> according Federated Search in Library context.
> Th
On Tue, Aug 27, 2013 at 2:03 AM, Paul Libbrecht wrote:
> Dan,
>
> if you're bound to federated search then I would say that you need to work
> on the service guarantees of each of the nodes and, maybe, create
> strategies to cope with bad nodes.
>
> paul
>
+1
I'll think on that.
, ...
The trick with Federated Search is to combine the results.
We offered three options to the users search surface:
- RoundRobin
- Relevancy
- PseudoRandom
--
View this message in context:
http://lucene.472066.n3.nabble.com/More-on-topic-of-Meta-search-Federated-Search-with-Solr-tp4085167p40
Dan,
if you're bound to federated search then I would say that you need to work on
the service guarantees of each of the nodes and, maybe, create strategies to
cope with bad nodes.
paul
Le 26 août 2013 à 22:57, Dan Davis a écrit :
> First answer:
>
> My employer is a library and do not have
Hi,
I would suggest for the following.
1. Create custom search connectors for each individual sources.
2. Connector will responsible to query the source of any type web, gateways
etc. and get the results & write the top N results to a solr.
3. Query the same keyword to solr and display the resu
One more question here - is this topic more appropriate to a different list?
On Mon, Aug 26, 2013 at 4:38 PM, Dan Davis wrote:
> I have now come to the task of estimating man-days to add "Blended Search
> Results" to Apache Solr. The argument has been made that this is not
> desirable (see Jo
First answer:
My employer is a library and do not have the license to harvest everything
indexed by a "web-scale discovery service" such as PRIMO or Summon.If
our design automatically relays searches entered by users, and then
periodically purges results, I think it is reasonable from a licens
Why not simply create a meta search engine that indexes everything of each of
the nodes.?
(I think one calls this harvesting)
I believe that this the way to avoid all sorts of performance bottleneck.
As far as I could analyze, the performance of a federated search is the
performance of the leas
I have now come to the task of estimating man-days to add "Blended Search
Results" to Apache Solr. The argument has been made that this is not
desirable (see Jonathan Rochkind's blog entries on Bento search with
blacklight). But the estimate remains.No estimate is worth much
without a desig
You are right, but here's my null hypothesis for studying the impact on
relevance.Hash the query to deterministically seed random number
generator.Pick one from column A or column B randomly.
This is of course wrong - a query might find two non-relevant results in
corpus A and lots of rele
The lack of global TF/IDF has been answered in the past,
in the sharded case, by "usually you have similar enough
stats that it doesn't matter". This pre-supposes a fairly
evenly distributed set of documents.
But if you're talking about federated search across different
types of documents, then wh
I've thought about it, and I have no time to really do a meta-search during
evaluation. What I need to do is to create a single core that contains
both of my data sets, and then describe the architecture that would be
required to do blended results, with liberal estimates.
>From the perspective o
15 matches
Mail list logo
