Return-Path: X-Original-To: archive-asf-public-internal@cust-asf2.ponee.io Delivered-To: archive-asf-public-internal@cust-asf2.ponee.io Received: from cust-asf.ponee.io (cust-asf.ponee.io [163.172.22.183]) by cust-asf2.ponee.io (Postfix) with ESMTP id 59B06200B57 for ; Fri, 22 Jul 2016 23:05:31 +0200 (CEST) Received: by cust-asf.ponee.io (Postfix) id 58324160A93; Fri, 22 Jul 2016 21:05:31 +0000 (UTC) Delivered-To: archive-asf-public@cust-asf.ponee.io Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by cust-asf.ponee.io (Postfix) with SMTP id 42E4D160A92 for ; Fri, 22 Jul 2016 23:05:29 +0200 (CEST) Received: (qmail 66312 invoked by uid 500); 22 Jul 2016 21:05:28 -0000 Mailing-List: contact commits-help@predictionio.incubator.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Reply-To: dev@predictionio.incubator.apache.org Delivered-To: mailing list commits@predictionio.incubator.apache.org Received: (qmail 66303 invoked by uid 99); 22 Jul 2016 21:05:28 -0000 Received: from pnap-us-west-generic-nat.apache.org (HELO spamd1-us-west.apache.org) (209.188.14.142) by apache.org (qpsmtpd/0.29) with ESMTP; Fri, 22 Jul 2016 21:05:28 +0000 Received: from localhost (localhost [127.0.0.1]) by spamd1-us-west.apache.org (ASF Mail Server at spamd1-us-west.apache.org) with ESMTP id E83DFC3AC0 for ; Fri, 22 Jul 2016 21:05:27 +0000 (UTC) X-Virus-Scanned: Debian amavisd-new at spamd1-us-west.apache.org X-Spam-Flag: NO X-Spam-Score: -4.497 X-Spam-Level: X-Spam-Status: No, score=-4.497 tagged_above=-999 required=6.31 tests=[KAM_ASCII_DIVIDERS=0.8, KAM_LAZY_DOMAIN_SECURITY=1, RCVD_IN_DNSWL_HI=-5, RCVD_IN_MSPIKE_H3=-0.01, RCVD_IN_MSPIKE_WL=-0.01, RP_MATCHES_RCVD=-1.287, T_FILL_THIS_FORM_SHORT=0.01] autolearn=disabled Received: from mx2-lw-eu.apache.org ([10.40.0.8]) by localhost (spamd1-us-west.apache.org [10.40.0.7]) (amavisd-new, port 10024) with ESMTP id TW5WEyWFGNyq for ; Fri, 22 Jul 2016 21:05:19 +0000 (UTC) Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by mx2-lw-eu.apache.org (ASF Mail Server at mx2-lw-eu.apache.org) with SMTP id B6405611F6 for ; Fri, 22 Jul 2016 21:04:59 +0000 (UTC) Received: (qmail 63674 invoked by uid 99); 22 Jul 2016 21:04:58 -0000 Received: from git1-us-west.apache.org (HELO git1-us-west.apache.org) (140.211.11.23) by apache.org (qpsmtpd/0.29) with ESMTP; Fri, 22 Jul 2016 21:04:58 +0000 Received: by git1-us-west.apache.org (ASF Mail Server at git1-us-west.apache.org, from userid 33) id 5CE04E058E; Fri, 22 Jul 2016 21:04:58 +0000 (UTC) Content-Type: text/plain; charset="us-ascii" MIME-Version: 1.0 Content-Transfer-Encoding: 8bit From: donald@apache.org To: commits@predictionio.incubator.apache.org Date: Fri, 22 Jul 2016 21:05:33 -0000 Message-Id: <7a9ffc63a6b54a73939b8e8f3665dcd9@git.apache.org> In-Reply-To: References: X-Mailer: ASF-Git Admin Mailer Subject: [37/51] [partial] incubator-predictionio-site git commit: [PIO-6] Clean up for ASF archived-at: Fri, 22 Jul 2016 21:05:31 -0000 http://git-wip-us.apache.org/repos/asf/incubator-predictionio-site/blob/734e6fcd/datacollection/eventmodel/index.html ---------------------------------------------------------------------- diff --git a/datacollection/eventmodel/index.html b/datacollection/eventmodel/index.html index 70106cb..428cd67 100644 --- a/datacollection/eventmodel/index.html +++ b/datacollection/eventmodel/index.html @@ -1,26 +1,4 @@ -Events Modeling
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Edit this page

This section explains how to model your application data as events.

Entity: it's the real world object involved in the events. The entity may perform the events, or interact with other entity (which became targetEntity in an event).

For example, your application may have users and some items which the user can interact with. Then you can model them as two entity types: user and item and the entityId can uniquely identify the entity within each entityType (e.g. user with ID 1, item with ID 1).

An entity may peform some events (e.g user 1 does something), and entity may have properties associated with it (e.g. user may have gender, age, email etc). Hence, events involve entities and there are two types of events, respectively:

  1. Generic events performed by an entity.
  2. Special events for recording changes of a n entity's properties
  3. Batch events

They are explained in details below.

1. Generic events performed by an entity

Whenever the entity performs an action, you can describe such event as entity "verb" targetEntity with "some extra information". The "targetEntity" and "some extra information" can be optional. The "verb" can be used as the name of the "event". The "some extra information" can be recorded as properties of the event.

The following are some simple examples:

  • user-1 signs-up
1
+Events Modeling

 
PredictionIO on Twitter PredictionIO on Facebook 

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-Event Server Overview

 
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Apache PredictionIO (incubating) offers an Event Server that collects data in an event-based style via a RESTful API. By default, Event Server uses Apache HBase as data store.
EventServer Highlight
What data should I collect?
The Event Server can collect and store arbitrary events. At the beginning of your project, it is recommended to collect as much data as you can. Later on, you can exclude data that are not relevant to your predictive model in Data Preparator.
Recommendation Engine
With Collaborative Filtering based Recommendation Engine, a common pattern is
1
user -- action -- item
-
 
 
where users and items have properties associated with them.
For example, for personalized book recommendation, some events to collect would be
 
     
  • User 1 purchased product X
    •  
  • User 2 viewed product Y
    •  
  • User 1 added product Z in the cart
    •  
 
User properties can be gender, age, location, etc. Item properties can be genre, author, and other attributes that may be related to the the user's preference.
Data collection varies quite a bit based on your application and your prediction goal. We are happy to assist you with your questions.
On this page
Edit this page
Apache PredictionIO (incubating) offers an Event Server that collects data in an event-based style via a RESTful API. By default, Event Server uses Apache HBase as data s
 tore.
EventServer Highlight
What data should I collect?
The Event Server can collect and store arbitrary events. At the beginning of your project, it is recommended to collect as much data as you can. Later on, you can exclude data that are not relevant to your predictive model in Data Preparator.
Recommendation Engine
With Collaborative Filtering based Recommendation Engine, a common pattern is
1
user -- action -- item
+
 
 
where users and items have properties associated with them.
For example, for personalized book recommendation, some events to collect would be
 
     
  • User 1 purchased product X
    •  
  • User 2 viewed product Y
    •  
  • User 1 added product Z in the cart
    •  
 
User properties can be gender, age, location, etc. Item properties can be genre, author, and other attributes that may be related to the the user's preference.
Data collection varies quite a bit based on your application and your prediction goal. We are happy to assist you with your questions.

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+_st('install','HaUfpXXV87xoB_zzCQ45');
\ No newline at end of file

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