I cannot find any option to achieve a verbatim azure/cognitive/bing Web search.
In my case the difference is trying to sift through tens of millions of irrelevant search results to find the 10 results that actually match my query literally.
Even though I am a paying customer, there is no support available. And the API documentation did not help either.
I would think it should be super easy to provide a verbatim search option. Is there one that I did not see?
I checked further and it seems for the Bing Search APIs - +"phrase" works and returns documents containing this phrase at the top. Just add + in front of what you have been trying. Support link is here: https://azure.microsoft.com/en-us/support/plans/.
I'm trying to do a wildcard search on Wikipedia but the search is not behaving the way the instructions say it should. Here's the advanced search help page:
https://en.wikipedia.org/wiki/Help:Advanced_search
As an example, it says this regarding a Wildcard search:
the query *stan will match Kazakhstan or Afghanistan or Stan Kenton.
However, when I attempt to do that search (or even click on the embedded link to that search), I only get
the page *stan does not exist
and it just lists a bunch of "Stan" entries starting with "Stan Laurel filmography."
Why would this feature not work? Am I missing something?
It does work, however because direct matches for "stan" are scored higher than words with it, Kazakhstan is waaaay down in results. You can try slightly narrowing the results with intitle:*stan however this is still bad. However, a quick check with k*stan shows that it works.
Conclusion: user-written help page has a bad example.
I would like to query two or three terms in order to locate them in Wikipedia´s entries. Specifically, I´m trying to see if some terms get repeated in the first paragraphs (abstract) across entries. Could be direct or through dbpedia. Thanks
Using Mediawiki API you can find articles that contain those keywords.
Try the API:Search documentation.
For doing what you want to do, also, you'd probably need to find the articles that have those keywords and then parse the text to check if they are in the first paragraphs.
With this:
?action=parse&page=Nicolas_Cage&prop=text§ion=0
you can get the HTML of the first section of a page (see this post).
I am trying to search for only people from Wikipedia and return them in some format (ideally using regex, but a simpler search is okay).
The following query is close, but doesn't allow me to include a specific search query and it appears to only included dead people (well I believe historic figures).
http://en.wikipedia.org/w/api.php?action=query&list=search&srsearch=wikipedia&srprop=timestamp&eititle=Template:Persondata
The following query works although I can't seem to limit the results to people only.
http://en.wikipedia.org/w/api.php?action=query&list=embeddedin&eititle=Template:Persondata&eilimit=100&format=xml&redirects
API sandbox |
You want to use Wikidata APIs for semantic searches. Example search for P31 → 5 ("is a human"), using the Wikidata Query Service: http://tools.wmflabs.org/wikidata-todo/autolist.html?q=CLAIM%5B31%3A5%5D
We've got Solr sat behind one of our client's Drupal 7 websites, and while it's working well, it returns too many results for what should be quite specific queries. (It also has relevance/weighting problems; but I'm hoping that solving this problem will remove the - literally - irrelevant results.)
For example, searching for the phrase 'particular phrase in london' should return the node with that as its title, quite high up; I don't even think that any other content should be returned. But I find that it's returning lots of content, purely on the fact that it mentions "London"!
Frivolously, searching for the ridiculous phrase 'piecrusts in london' returns a lot of results too, apparently just because they mention London. No content on the site mentions actual piecrusts.
When I search for 'particular phrase in london', here are the parameters that end up in the catalina.out log on the server (whitespace added for clarity):
{spellcheck=false&facet=true&f.im_field_health_topic.facet.mincount=1
&facet.mincount=1&f.ds_created.facet.date.gap=%2B1YEAR
&spellcheck.q=particular+phrase+in+london
&qf=taxonomy_names^2.0&qf=path_alias^5.0&qf=content^40&qf=label^21.0
&qf=tos_content_extra^1.0&qf=ts_comments^20&qf=tm_vid_3_names^200
&facet.date=ds_created
&f.ds_created.facet.date.start=1970-01-01T00:00:00Z/YEAR
&f.bundle.facet.mincount=1&hl.fl=content,ts_comments
&json.nl=map&wt=json&rows=10&fl=id,entity_id,entity_type,bundle,bundle_name,
label,is_comment_count,ds_created,ds_changed,score,path,url,is_uid,
tos_name,tm_node,zs_entity
&start=0&facet.sort=count&f.bundle.facet.limit=50&q=special+phrase+in+london
&f.ds_created.facet.date.end=2012-01-01T00:00:00Z%2B1YEAR/YEAR
&bf=recip(ms(NOW,ds_created),3.16e-11,1,1)^150.0
&facet.field=im_field_health_topic&facet.field=bundle
&f.im_field_health_topic.facet.limit=50&f.ds_created.facet.limit=50}
hits=1998 status=0 QTime=14
Note that these parameters have been built by Drupal's Apache Solr module; I don't believe we've got any particular custom code of our own that's doing anything to it.
This corresponds to the following URL, if entered directly in the browser:
http://example.com:8081/solr/CLIENT/select?spellcheck=false&facet=true&f.im_field_health_topic.facet.mincount=1&facet.mincount=1&f.ds_created.facet.date.gap=%2B1YEAR&spellcheck.q=particular+phrase+in+London&qf=taxonomy_names^2.0&qf=path_alias^5.0&qf=content^40&qf=label^21.0&qf=tos_content_extra^1.0&qf=ts_comments^20&qf=tm_vid_3_names^200&facet.date=ds_created&f.ds_created.facet.date.start=1970-01-01T00:00:00Z/YEAR&f.bundle.facet.mincount=1&hl.fl=content,ts_comments&json.nl=map&wt=json&rows=10&fl=id,entity_id,entity_type,bundle,bundle_name,label,is_comment_count,ds_created,ds_changed,score,path,url,is_uid,tos_name,tm_node,zs_entity&start=0&facet.sort=count&f.bundle.facet.limit=50&q=particular+phrase+in+London&f.ds_created.facet.date.end=2012-01-01T00:00:00Z%2B1YEAR/YEAR&bf=recip(ms(NOW,ds_created),3.16e-11,1,1)^150.0&facet.field=im_field_health_topic&facet.field=bundle&f.im_field_health_topic.facet.limit=50&f.ds_created.facet.limit=50
This URL returns nearly 2000 results - that's most of the content on the site! I've experimented with removing each query parameter at a time, and the only one to make any difference seems to be qf and q: if I remove qf, zero results; if I remove q, I get more results back!
I guess there are two questions here:
Is there anything in these parameters that tell Solr "don't worry if 'particular phrase', or 'piecrusts' appears: just collate the results for 'london'" and then order by relevancy? I would add that I think 'in' is mentioned in the stopwords file, so we can probably ignore the effect of that (?)
Or is this something in the (standard Drupal) schema that I need to change?
I appreciate that sometimes search is better for the visitor if it's inclusive; Google does return results even if it doesn't find perfect matches. But, stopwords and stemming aside, the client does require that searches return only results where all words appear in the content.
As mentioned in the post at http://drupal.org/node/1783454, the Apache Solr Search Integration module makes use of the mm param, which is more or less configured to effect rankings by how closely the keywords are in the dataset. Looking through the docs there are other ways you can use the parameter to effect rankings as well. Therefore the results produced by Apache Solr Search Integration are weighted more closely to the AND operator even though it will return more results as you add more keywords. The benefit of this param is that in cases where the user enters keywords that are too restrictive, results will still be returned. Displaying no results is a really quick way to guide people away from your site.
How are you displaying the search ?
Maybe you could solr views to limit the search range ?
http://drupal.org/project/apachesolr_views
thanks
Nick