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Rakuten Technology Conference 2013 "Rakuten Category" Suguru Suzuki, Yuhei Nishioka (Rakuten)
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Rakuten CategoryVol.01 Oct/26/2013Yuhei Nishioka / Suguru SuzukiRakuten Inc.http://www.rakuten.co.jp/
2
Agenda
1.Rakuten Category- Introduction -
2.Measurement/Modification- Approach for Category design -
3.Release- Standardization -
3
Self-Introduction
Suguru SuzukiJapan Ichiba SectionJapan Mall GroupRakuten Ichiba Development Department
• Application Engineer• Joined Rakuten in 2007• Ichiba TOP/ Rakuten
Search(All devices)
Yuhei NishiokaRakuten Institute of Technology
• Chief Technologist• Joined Rakuten in 2008• Semantic Web,
Recommender System
Rakuten Category- Introduction -
Rakuten Category
5
Rakuten Category
What’s Category??
Category??
6
カテゴリーは、事柄の性質を区分する上でのもっとも基本的な分類のことである。
In metaphysics (in particular, ontology), the different kinds or ways of being are called categories of being or simply categories.
Rakuten Category
Source of Quote : wikipedia http://ja.wikipedia.org/wiki/%E3%82%AB%E3%83%86%E3%82%B4%E3%83%AA
Rakuten’s Category is…
Sales area =“ 売り場”
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Rakuten Category
Rakuten Search
CategoryRanking
Category
ReviewCategory
BooksCategory
CategoryAuction
Category
TOP/Genre TOP
Category
Racoupon/coupon search
Category
And more and more….
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Rakuten Category
Data Number
Category in Rakuten Ichiba 50,896 genres
Using Category Service 50 service
Using Category Application 100 application
Effective Service of using Category(Genre/Tag)
Auction
RMS
SearchEngine
kobo
Basket
Review
Rakuten Search
Books
Ranking
Advertisement
TOP page
Item Page
Affiliate
BrowsingHistory
Web Service
Super DB
GMSReport
Auto
Racoupon
A lot of service useCategory data!
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Rakuten Category
Good Categorize
Catch up the trend
Easy to navigate User
Big factor to increase sales in each items.
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Rakuten Category
User Come across items
Shop Sell itemsRakuten Sell items
Data analysis
Benefit!!
11
Rakuten Category
Cycle of Category Strategy
Measurements
ReleaseModification
Need toHigh Speed!!
Measurement/Modification
Measurement/Modification- Approach for Category design -
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Measurement/Modification
Measurements
ReleaseModification
POINT
POINT
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Measurement/Modification
Measurement on WEB-toolTree view Item countSales volumeRanking data
Show more detail!!
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Data-Driven Optimization
Modify Category by Analyzing User’s Queries
Past Example of data-driven optimization
….ホットプレート(Hot Plate)…
タジン鍋(Tagines)
No responding genre
You can find “ タジン鍋”without using search
List of high frequency queries
Create new category(a couple of years ago)
Already existing in Rakuten Category Tree
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Types of queries
Needs browsing function for not only category tree but also other attributes
Ratio of Query Types
Source: User Queries tat Rakuten Ichiba in 2013
Podcut Category
Brand
Merchant
Spec
Character
Others
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Master Database
Create new master database for brand, color and so on
Data Structure behind Navigation
BrandMaster. a
Unified Brand Master
IntegrationBrand
Master. b
BrandMaster. c
Category…..…..…..
Brand…..…..…..
Color…..…..…..
Color Master
Category Tree
Already Exist
…
NavigationMaster DataData Source
New
New
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The difficulty identifying brand
Brand name matching is very effective. But must solve 2 major problems
2 major technical problems in brand name matching
• Different Things with the Same Name• カリタ
• The Same Thing with Different Names• Samsung• サムスン
http://www.kalita.co.jp/
http://www.carita.jp/
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Check by hand
Brand name matching is very effective. But must solve 2 major problems
Data Process
Original Matching Algorithm- Title match- Synonym check- Ambiguous word check- Use other attribute- … chec
k
Result
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Check by hand with few costs
OpenRefine is very helpful
ID Name
xxx SONY
yyy カリタ
…. ….
Original Matching Algorithm
Other Master Data
SONY [ Matched ]
Karita [ Candidate1 ] CARITA [ Candidate 2]
API for Open Refine
Web Interface
Server side
http://openrefine.org/
Useful Open Source Tool
http://www.carita.jp/source
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Color Master
Building color dictionary automatically as much as possible
Color Dictionary
黒
black.
1,871 color names
黒色• Image Processing
• Natural Language Processing
Black
Blue
blue
navy
.
16 color groups
..
.
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Tagging Data for each item
Structured Data
Category Brand Color
Item ID Category Brand Color …
xxxx
….
Merchant Input
Extract AutomaticallyFrom item description
(in research)
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Attribute value extraction
• Generate extraction rules using attribute value database constructed from table data
Item page includinga dictionary entry
Rulewine from x => x is a Region
Chateau d’Issan 1994This is a wine from Margaux....
:<Region, Margaux><Color, White> :
DatabaseAnnotation
Values not included in the database can be captured.
Table data
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Measurement/Modification
Modification on WEB-tool
Drag and DropEasy to modify!!
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Measurement/Modification
Old modification styleExtra
Hand-made…!
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Measurement/ModificationExtra
Problem
Achieved limit counts by excel
…orz
Old modification style
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Measurement/Modification
Good Categorize =A huge benefit Very Important phase Need to survey trend and data
optimization
Release
Release- Standardization -
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Release
Measurements
ReleaseModification
POINT
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Release
Measurements
ReleaseModification
Need it more rapidly!!
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Release
Hard to release Category dataCategory data has over 15 DB…Deliver its data to all 50 service.
Auction
RMS
SearchEngine
kobo
Basket
Review
Rakuten Search
Books
Ranking
Advertisement
TOP page
Item Page
Affiliate
BrowsingHistory
Web Service
Super DB
GMSReport
Auto
Racoupon
Have over 15 DB....
Deliver data to all service
Add new servicesometime
Extra - Before
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Extra - Before Release
Show the Maintenance time tableWhen Category Restructuring maintenance.Complicated!!!Related Category Restructuring task
is almost 300!!
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Release
Easy to release by all servicemore speedy
ServiceA
・・・・
ServiceB
ServiceC
ServiceD
ServiceE
Already Automation In Progress for Automation
Now improving!
API
CategoryData
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Release
■System Reconstruction used by APIBefore In
Progress
Test and operate by each service
ServiceA serviceB
serviceD serviceE
serviceC
・・・・
Release in Regular Maintenance
6monthMaking data by management tool
Release in week
ServiceA serviceB serviceC
・・・・
APIReflect new Data used by API
Making data by handmade
Share data by dump or excel
Every week
serviceD serviceE
CategoryData
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Release
More easily more Speedy!!
Auction
RMS
SearchEngine
kobo
Basket
Review
Rakuten Search
Books
Ranking
Advertisement
TOP page
Item Page
Affiliate
BrowsingHistory
Web Service
Super DB
GMSReport
Auto
Racoupon
CategoryAPI
For operation freeGet rid of dependency in each service
CategoryData
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■Real Time reflection
iPhone5s
Register
Real Time releasedwhen needed.
Real Time reference
Can be released Category Data andsearch it by “Real Time” on Rakuten Search.
Release
37
■Real Time reflection
iPhone5s
Register
Can be released Category Data andsummarize it on Ranking.
Releasedas a daily/weekly
Ranking data.
Release
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■Real Time reflection
iPhone5s
Register
Can be createdLanding-page
used bynew Categorydata
Can be released Category Data andCreate Landing-page.
Release
39
Finally
Measurements
ReleaseModification
Standardization forcycle of Improvement
40
Finally
User Come across items
Shop Sell itemsRakuten Sell items
Data analysis
Benefit!!Category optimization ismade everyone happy!!
41
Thank you for your Listening!!Finally
If you have any idea or question, Please contact us.Let’s talk about Category with us!!
Yuhei Nishioka
@nishiokamegane
Suguru Suzuki
@sugsuzuki