Is there an API to get results similar to Google's "people also search for"? - semantic-web

Question

I'm looking for an API that would give similar results to the Google's "people also search for" feature. So that, for instance, when I search for Stanley Kubrik, I see all the other film directors that people search for.
I know about the Freebase API but it simply provides information about the search item, not what other search items it may be related to.
There is also a TargetingIdeaSelector tool in Google AdWords API that shows related keywords, but that doesn't really range the results semantically.
Finally, there's a very simple Bing API that shows related searches (also here), but, again, it does not range information semantically.
Do you know of any API or maybe if there is something like that in Google's APIs that would show me related searches ranged semantically?

Answer 1

Google used to offer such API but it was decapricated a few years back. I am unsure why this was the case but my guess is because it housed no real benefit for them and likely cost a lot to maintain. most major search engines tend to not have search API's in my experience.
You could however try an make your own using a PHP and DOM Parser to parse the results from somewhere like google and export the data out as JSON.
available for download here http://simplehtmldom.sourceforge.net
This should pull out all the links from Google which you can then format out. You can parse all data and can target objects see the documentation for more
$search = $_GET['search'];
> $google_search = file_get_html('https://www.google.co.uk/?gws_rd=ssl#q=' . $search);
>
> foreach($google_search->find('a') as $item) {
> echo $item->href . '<br>';
> }
Hope that helps

Answer 2

The results that Google shows is based on massive amount of data that i guess built on "what X who searched for Y also searched for", "what other people similar to X who also searched for Y searched for" and so on. In addition maybe there is some reliance on semantic information coming from Freebase.
On an initiative to understand what kind of properties Google shows in their infoboxes, i.e. Why when we search for France we get a card with map, flag, capital, population ... etc. amongst the hundreds of properties relate to France i created a "Knowledge Base Extractor " that is able to parse the Google infobox and expose the data as RDF using the Fresnel Vocabulary.
The Algorithm implemented is the following:
Query DBpedia for all concepts (types) for which there is at least one instance that has a link to a Freebase ID
For each of these concepts pick (n) instances randomly
For each instance, issue a Google Search query:
if an infobox is available -> scrap the infobox to extract the properties
if no infoxbox is available, check if Google suggests "do you mean ... ?" and if so, traverse the link and look for an infobox
if no infobox or correction is available, disambiguate the concept (type) used in the search query and check if an infobox is returned
if Google suggests disambiguation in an infobox parse all the links in it -> it is best to find which suggestion maps to the current data-type we are using -> check the Freebase - DBpedia mappings
Cluster properties for each concept
I also capture that "people searched for" section, but you might also want to tweak it a bit more.
Also note that you might want to check the CSS selectors for the infobox as Google changes them often (maybe auto-generated). This is done in the options.json
"knowledgeBox" : "#kno-result",
"knowledgeBox_disambiguate" : ".kp-blk",
"property" : "._Nl",
"property_value" : ".kno-fv",
"label" : ".kno-ecr-pt",
"description" : ".kno-rdesc",
"type" : "._kx",
"images" : ".bicc",
"special_property" : ".kno-sh",
"special_property_value" : "._Zh",
"special_property_value_link" : "a._dt"