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From arun abraham <arunabraham...@gmail.com>
Subject Re: Reg:-Integrating Mahout with Solr
Date Sun, 02 Apr 2017 01:21:42 GMT
Hi,

Thanks Pat for the reply.

I am trying to implement item based recommendation as the first step.When
the user searches with a keyword(using Solr),not only it should return
keyword matching results(already implemented along with other search
features of Solr) but also related documents(recommended).

I believe implementing item based recommendation will be a good learning
curve towards implementing the user based recommendation or Behavioral
 based.As  a first step I am trying to recommend min of two documents(As my
Solr document index is ~100 docs).

I understood that in the above scenario,first step is to provide the Solr
index to mahout to read and will generate a vector file from it.
It will be helpful if I get guidance on the integration steps to follow for
the same.

Thanks and Regards,
Arun


On 1 April 2017 at 23:46, Pat Ferrel <pat@occamsmachete.com> wrote:

> You want to create “Behavioral Search”? This is where you boost items that
> have the search terms in them more likely to be favored by the individual
> user?
>
> You want to use the CCO algorithm in Mahout. You need to collect
> behavioral information like conversions, detailed page views, etc. Run each
> event through CCO and you get a collection of “indicators” as item
> attributes. Augment the Solr index with fields (indicators) attached to
> item documents. Then at query time supply the search terms as a “must
> match” and use user history as the query segment against the corresponding
> indicator fields as a “should match” with some boosting factor.
>
> CCO is here: http://mahout.apache.org/users/algorithms/intro-
> cooccurrence-spark.html <http://mahout.apache.org/users/algorithms/intro-
> cooccurrence-spark.html>
> and a post on Personalizing Search here: http://www.actionml.com/blog/
> personalized_search <http://www.actionml.com/blog/personalized_search>
>
> BTW Do you have a recommender running? If not that is likely to generate
> almost an order of magnitude better results than Behavioral Search. From
> Industry wisdom and experience, implement a recommender first, then augment
> search. On E-Commerce data we have reported results of 10-30% conversion
> lift from recommendations and ~3% for Behavioral Search. 3% is significant
> but requires you to gather the same info that it takes to do a recommender
> so why not do a recommender first.
>
> There is an almost turnkey recommender that uses CCO here:
> http://actionml.com/ur It uses Elasticsearch but is standalone, not
> integrated into any search tech you use elsewhere.
>
>
> On Mar 31, 2017, at 9:30 PM, arun abraham <arunabraham100@gmail.com>
> wrote:
>
> Hi All,
>
> I am trying to integrate Apache mahout with Solr.I have created a search
> application using Solr which has spellcheck,type ahead suggestions
> functionalities.I have a new requirement to display recommendations( from
> index which has ~100 docs ) for a specific search(keyword based).Is it
> possible to recommend docs or links from web together with the indexed
> data?
> Kindly guide me on the possibilities for the same also on the integration
> part.
>
> Thanks and Regards,
> Arun
>
>

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