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1
Recent Activities for the Rakuten
Global e-commerce
Atividades de Pesquisa da Rakuten
para o e-commerce Global
Rakuten Institute of Technology, New York
2
Rakuten Institute of Technology
Turning emerging and growing new technology seeds
into new business/service opportunities
to enrich the internet life (& real life) all over the world
Mission
The Next Reality
- New reality through emerging technologies -
Concept Tokyo & NY
Strategic R&D organization for Rakuten group
3
Our goal
How was the
carrot you got
yesterday?
Today this fresh
lettuce is good
Recommendation
You will take
a vacation?
The travel agent
over there gives
good service
Affiliation
You are on diet,
but like sweet
food?
This sweet tomato
is good for your
health
Personalization
Old-fashioned vegetable shop
owner
4
Our goal
You want to
know the
vegetable in
this photo…
It is an artichoke.
Image
recognition
You can boil it
and eat it with
mayonnaise
World knowledge
Recently, it is very
popular among
young people
Opinion mining
Old-fashioned vegetable shop
owner
5
Create happy shopping experiences
Hints from a legendary & successful owner at a market
Understand language
Master his products
Understand the customers
World Knowledge
Recognize image, video
Remember for the future
Manipulate knowledge
Think, inference, analysis
Situation adaptation
Friendly service
NLP
Multi-media
Data
Semantic
Data
I/F
AI
Infrastructure
6
Research Topics
1. Rakuten Hub Category
2. Category Correction
3. Attribute Extraction
7
Research Topics
1. Rakuten Hub Category
2. Category Correction
3. Attribute Extraction
8
Different Category Structures of Rakuten Group
Companies
9
Hub and Spoke Model
HUB
10
Global vs. Local
Problem: Culture/Market dependency
We need one uniform DB structure = Global Catalog
Organize globally Adapt Locally
Sports Equipment
PelotaBaseball
11
Overview
attribute value
Product information by
Attributes and values
Product types
Product category for display is
decided by “product types” and a set
of attribute values
Mapping
R-HC Local Hierarchy
12
Definition of Global Category
135 top categories
Culture/country independent
13
Definition of Attribute (bag)
Set of attributes
for each category
14
Tool to be provided
15
Research Topics
1. Rakuten Hub Category
2. Category Correction
3. Attribute Extraction
16
2. Category Correction
Muffler
Sake
NOISE!
Muffler
Muffler
Users are annoyed, Merchants are in trouble
→ Detecting the misplaced products
→ Reassigning them into the right genres
Many products are assigned into a wrong category
17
Bottle
720ml
Japan
Delicious
Tengumai
light
Japanese SakeJapanese Sake
Tengumai
Note:
“Tengumai” is a famous
Japanese sake (rice wine)
The words, which are
assigned into only one
category automatically
dictionary
Definitive Category Words (DCW)
Modified TF/IDF strategies
18
Actual Contributions
0
10
20
30
40
Jul. Aug. Sep. Oct. Nov.
GMS
0
10
20
30
40
Jul. Aug. Sep. Oct. Nov.
GMS
(1) 2 big merchants
2 million products  
(2011/9)
FIX Merchant A FIX
2011 2011
(3) Expanding to more categories
(2) 2 categories, which include 1,000 merchants
1 million products (2011/11)
Merchant B
→ Contributed to GMS
5 million products (2012/10)
19
Research Topics
1. Rakuten Hub Category
2. Category Correction
3. Attribute Extraction
20
3. Automatic Attribute Extraction
Unsupervised Extraction of
Attribute and value from
product description
Attribute Value
Color Red
County Chile
Grape Cabernet franc,
Merlot,
Vintage 2009
21
Product information is embedded in texts
38% 62%
22
Synonym Detection
• Attribute names that share a popular value and
don’t appear in the same table are synonym
Region
France, German, Italy …
Alcohol
District
Temperature
for drinking
15 degree, 8 degree …
Synonym
Not Synonym
23
KB for wine category
Grape Type Volume Region Winery Taste
Chardonnay 750ML France Farnese Dry
Chardonnay
100%
720ML Italy Mas de
Monistrol
Full body
Merlot 375ML Spain Leroy Medium body
Riesling 500ML Chile M. Chapoutier Slightly sweet
Syrah 1500ML German Mastroberardino Sweet
Grenache 360ML Australia Santero Medium dry
Merlot 200ML America Saltarelli Extremely sweet
Tempranillo 3000ML Bordeaux Cavicchioli Medium dry
Sangiovese 1800ML Champagne Fontodi Red Full body
Syrah100% 1000ML Argentina Ca'Rugate Middle sweet
24
Our Goal
Technologies for
Happy
Shopping
Experiences
25
Our Goal

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Atividades de Pesquisa da Rakuten para o E-commerce Global - Satoshi Sekine / Diretor do Instituto de Tecnologia da Rakuten NY

  • 1. 1 Recent Activities for the Rakuten Global e-commerce Atividades de Pesquisa da Rakuten para o e-commerce Global Rakuten Institute of Technology, New York
  • 2. 2 Rakuten Institute of Technology Turning emerging and growing new technology seeds into new business/service opportunities to enrich the internet life (& real life) all over the world Mission The Next Reality - New reality through emerging technologies - Concept Tokyo & NY Strategic R&D organization for Rakuten group
  • 3. 3 Our goal How was the carrot you got yesterday? Today this fresh lettuce is good Recommendation You will take a vacation? The travel agent over there gives good service Affiliation You are on diet, but like sweet food? This sweet tomato is good for your health Personalization Old-fashioned vegetable shop owner
  • 4. 4 Our goal You want to know the vegetable in this photo… It is an artichoke. Image recognition You can boil it and eat it with mayonnaise World knowledge Recently, it is very popular among young people Opinion mining Old-fashioned vegetable shop owner
  • 5. 5 Create happy shopping experiences Hints from a legendary & successful owner at a market Understand language Master his products Understand the customers World Knowledge Recognize image, video Remember for the future Manipulate knowledge Think, inference, analysis Situation adaptation Friendly service NLP Multi-media Data Semantic Data I/F AI Infrastructure
  • 6. 6 Research Topics 1. Rakuten Hub Category 2. Category Correction 3. Attribute Extraction
  • 7. 7 Research Topics 1. Rakuten Hub Category 2. Category Correction 3. Attribute Extraction
  • 8. 8 Different Category Structures of Rakuten Group Companies
  • 9. 9 Hub and Spoke Model HUB
  • 10. 10 Global vs. Local Problem: Culture/Market dependency We need one uniform DB structure = Global Catalog Organize globally Adapt Locally Sports Equipment PelotaBaseball
  • 11. 11 Overview attribute value Product information by Attributes and values Product types Product category for display is decided by “product types” and a set of attribute values Mapping R-HC Local Hierarchy
  • 12. 12 Definition of Global Category 135 top categories Culture/country independent
  • 13. 13 Definition of Attribute (bag) Set of attributes for each category
  • 14. 14 Tool to be provided
  • 15. 15 Research Topics 1. Rakuten Hub Category 2. Category Correction 3. Attribute Extraction
  • 16. 16 2. Category Correction Muffler Sake NOISE! Muffler Muffler Users are annoyed, Merchants are in trouble → Detecting the misplaced products → Reassigning them into the right genres Many products are assigned into a wrong category
  • 17. 17 Bottle 720ml Japan Delicious Tengumai light Japanese SakeJapanese Sake Tengumai Note: “Tengumai” is a famous Japanese sake (rice wine) The words, which are assigned into only one category automatically dictionary Definitive Category Words (DCW) Modified TF/IDF strategies
  • 18. 18 Actual Contributions 0 10 20 30 40 Jul. Aug. Sep. Oct. Nov. GMS 0 10 20 30 40 Jul. Aug. Sep. Oct. Nov. GMS (1) 2 big merchants 2 million products   (2011/9) FIX Merchant A FIX 2011 2011 (3) Expanding to more categories (2) 2 categories, which include 1,000 merchants 1 million products (2011/11) Merchant B → Contributed to GMS 5 million products (2012/10)
  • 19. 19 Research Topics 1. Rakuten Hub Category 2. Category Correction 3. Attribute Extraction
  • 20. 20 3. Automatic Attribute Extraction Unsupervised Extraction of Attribute and value from product description Attribute Value Color Red County Chile Grape Cabernet franc, Merlot, Vintage 2009
  • 21. 21 Product information is embedded in texts 38% 62%
  • 22. 22 Synonym Detection • Attribute names that share a popular value and don’t appear in the same table are synonym Region France, German, Italy … Alcohol District Temperature for drinking 15 degree, 8 degree … Synonym Not Synonym
  • 23. 23 KB for wine category Grape Type Volume Region Winery Taste Chardonnay 750ML France Farnese Dry Chardonnay 100% 720ML Italy Mas de Monistrol Full body Merlot 375ML Spain Leroy Medium body Riesling 500ML Chile M. Chapoutier Slightly sweet Syrah 1500ML German Mastroberardino Sweet Grenache 360ML Australia Santero Medium dry Merlot 200ML America Saltarelli Extremely sweet Tempranillo 3000ML Bordeaux Cavicchioli Medium dry Sangiovese 1800ML Champagne Fontodi Red Full body Syrah100% 1000ML Argentina Ca'Rugate Middle sweet

Editor's Notes

  1. Rakuten has actually over 2000 engineers for IT infrastructure and service development. You know, Rakuten has tons of businesses all over the world, and, we need many many engineers to sustain that. In addition, we have also research institute. That is named “RIT”, standing for Rakuten Institute of Technology. We recruit computer science researchers, mainly phD and are trying to utilize academic knowledge, So as to – For the growth of e-commerce and growth of Rakuten
  2. In order for us to become a global market place, we need to handle items from all over the world and to all over the world, hence we need one uniform database structure. This is the "global catalog" However, there is a serious problem, which have just like political parties, contradicting policies. We have to organize all items globally, but on the other hand we have to adapt locally. In order to solve this problem, we are designing the Hub and spoke model. It has a hub, the item DB in the middle, and a spoke represents an individual local market. For example, "Sports equipment" can be acceptable across different markets, but individual sports, such as baseball or pelota are culture dependent, so they should be treated locally. We are planning to build the first version of the model this summer. 
  3. We have applied 2 methods and working on another method. First method is that we have fixed over 2 million noise products from 2 big merchants . This fixing helped them increase their GMS. Second method is that we have fixed over 1 million noise products in 2 large category groups, which are DIY tools and motor cycle categories. These noise corrections also helped GMS to increase 400 million yens according to the number estimated by the marketing team. I'm currently developing another method in Japanese and German Ichiba. My goal is to fix all noise products all over the rakuten world. (--> PREVENTING noise from happening) 