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Posted to user@predictionio.apache.org by Masha Zaharchenko <ma...@gmail.com> on 2017/02/27 11:48:50 UTC

New items in UR

Hi, everyone!
I want to use UR to get  scores for items in search results(to range them). But it`s possible that an item hasn`t got any interactions yet(hasn`t been viewed or purchased, etc.).
So I have the following question:
Will an item with no events be included in recommendations based only on its properties or will it be ignored?
Thanks,
Maria

Re: New items in UR

Posted by Pat Ferrel <pa...@occamsmachete.com>.
We have an in-house Template to implement “Behavioral Search” with the algo inside the UR called Correlated Cross-Occurrence. It allows you to augment your Search index, which usually contains mainly content from items. These augmentation fields have information about what item other people searched for or bought or whatever events you track. In the Search you then use the search the user typed in as well as other events they have in their history. 

When you make the search it find items with the search terms, as well as items the user is likely to convert on AND items that other people have searched and converted but with terms may match one the other people used. The later bit means that if there is a term people use that may not be in the content but is common, it will be put in the index to augment it. This could be slang, a common misspelling, or nicckname for the item. 

We call this “Behavioral Search” because the augmentation data comes from either other people’s behavior or the individual’s behavior. In the blog post below, we make a slight distinction between Personalized Search and Augmented Search because one uses user-specific data in the query and the other just uses other people’s data and so is not “personalized”. In practice it’s almost always better to use both.

TLDR; Behavioral Search will return items based on their content alone, if no behavioral match is found. it will boost items that the user is likely to convert on. Boost here means that it will return items with the search terms but favor items with the right behavioral data when available.

http://actionml.com/blog/personalized_search <http://actionml.com/blog/personalized_search>


On Feb 27, 2017, at 3:48 AM, Masha Zaharchenko <ma...@gmail.com> wrote:

Hi, everyone!
I want to use UR to get  scores for items in search results(to range them). But it`s possible that an item hasn`t got any interactions yet(hasn`t been viewed or purchased, etc.).
So I have the following question:
Will an item with no events be included in recommendations based only on its properties or will it be ignored?
Thanks,
Maria