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From Nasos Papageorgiou <at.papageorg...@gmail.com>
Subject RE: UR: build/train/deploy once & querying for 3 use cases
Date Thu, 10 May 2018 14:01:59 GMT
Hi all,
to elaborate on these cases, the purpose is to create a UR for the cases of:

1.       “User who Viewed this item also Viewed”

2.       “User who Bought this item also Bought”

3.       “User who Viewed this item also Bought ”

while having Events of Buying and Viewing a product.
I would like to make some questions:

1.       On Data source Parameters, file: events.json: There is no matter
on the sequence of the events which are defined. Right?

2.       If I specify one Event Type on the “eventNames” in Algorithm
section (i.e. “view”)  and no event on the “blacklistEvents”,  is the
second Event Type (i.e. “buy”) specified on the recommended list?

3.       If I use only "user" on the query, the "item case" will not be
used for the recommendations. What is happening with the new users in that
case?   Shall I use both "user" and "item" instead?

4.        Values of less than 1 in “UserBias” and “ItemBias” on the query
do not have any effect on the result.

5.        Is it feasible to build/train/deploy only once, and query for all
3 use cases?


6.       How to make queries towards the different Apps because there is no
any obvious way in the query parameters or the URL?

Thank you.



*From:* Pat Ferrel [mailto:pat@occamsmachete.com]
*Sent:* Wednesday, May 09, 2018 4:41 PM
*To:* user@predictionio.apache.org; gerasimos xydas
*Subject:* Re: UR: build/train/deploy once & querying for 3 use cases



Why do you want to throw away user behavior in making recommendations? The
lift you get in purchases will be less.



There is a use case for this when you are making recommendations basically
inside a session where the user is browsing/viewing things on a hunt for
something. In this case you would want to make recs using the user history
of views but you have to build a model of purchase as the primary indicator
or you won’t get purchase recommendations and believe me recommending views
is a road to bad results. People view many things they do not buy, putting
only view behavior that lead to purchases in the model. So create a model
with purchase as the primary indicator and view as the secondary.



Once you have the model use only the user’s session viewing history in the
as the Elasticsearch query.



This is a feature on our list.




From: gerasimos xydas <gerasimos.xydas@gmail.com>
<gerasimos.xydas@gmail.com>
Reply: user@predictionio.apache.org <user@predictionio.apache.org>
<user@predictionio.apache.org>
Date: May 9, 2018 at 6:20:46 AM
To: user@predictionio.apache.org <user@predictionio.apache.org>
<user@predictionio.apache.org>
Subject:  UR: build/train/deploy once & querying for 3 use cases



Hello everybody,

We are experimenting with the Universal Recommender to provide
recommendations for the 3 distinct use cases below:

- Get a product recommendation based on product views
- Get a product recommendation based on product purchases
- Get a product recommendation based on previous purchases and views (i.e.
users who viewed this bought that)

The event server is fed from a single app with two types of events: "view"
and "purchase".

1. How should we customize the query to fetch results for each separate
case?
2. Is it feasible to build/train/deploy only once, and query for all 3 use
cases?


Best Regards,

Gerasimos

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