[RakutenTechConf2013] [B-3_3] Rakuten Category
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This document discusses Rakuten's category system and efforts to improve it. It begins with an introduction to categories and an overview of how Rakuten's category data is used across 50 services. It then discusses the importance of ongoing measurement, modification, and rapid release of category data. The authors describe automating processes for measuring category performance from user data, modifying the category tree structure based on analysis, and releasing updates through standardized APIs. The goal is to continually optimize categories based on trends and make updates available in real-time and weekly to better serve users and merchants.
![Check by hand with few costs
OpenRefine is very helpful
Server
side
Original Matching Algorithm
API for Open Refine
Web
Interface
ID
Name
Useful
Open Source Tool
Other Master Data
xxx
SONY
SONY [ Matched ]
yyy
カリタ
Karita [ Candidate1 ]
CARITA [ Candidate 2]
….
….
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[RakutenTechConf2013] [B-3_3] Rakuten Category
- 1. Rakuten Category Vol.01 Oct/26/2013 Yuhei Nishioka / Suguru Suzuki Rakuten Inc. http://www.rakuten.co.jp/
- 2. Agenda 1.Rakuten Category - Introduction - 2.Measurement/Modification - Approach for Category design - 3.Release - Standardization - 2
- 3. Self-Introduction Suguru Suzuki Japan Ichiba Section Japan Mall Group Rakuten Ichiba Development Department Yuhei Nishioka Rakuten Institute of Technology • Chief Technologist • Application Engineer • Joined Rakuten in 2007 • Joined Rakuten in 2008 • Semantic • Ichiba TOP/ Rakuten Web, Recommender Search(All devices) System 3
- 4. Rakuten Category Rakuten Category - Introduction -
- 6. Rakuten Category 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. 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” 6
- 7. Rakuten Category Rakuten Search Review Category Category Ranking Racoupon/coupon search Category TOP TOP/Genre Category Books Category Category Category Auction Category And more and more…. 7
- 8. 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) RMS GMS Report TOP page Search Engine Rakuten Search Web Service Advertisement Auction Review Books Racoupon kobo A lot of service use Category data! Auto Browsing History Super DB Affiliate Ranking Basket Mail Item Page 8
- 9. Rakuten Category Catch up the trend Good Categorize Easy to navigate User Big factor to increase sales in each items. 9
- 10. Rakuten Category Benefit!! User Come across items Shop Sell items Rakuten Sell items Data analysis 10
- 11. Rakuten Category Cycle of Category Strategy Measurements Modification Need to High Speed!! Release 11
- 12. Measurement/Modification Measurement/Modification - Approach for Category design -
- 14. Measurement/Modification Measurement on WEB-tool Tree view Item count Sales volume Ranking data Show more detail!! 14
- 15. Data-Driven Optimization Modify Category by Analyzing User’s Queries Past Example of data-driven optimization List of high frequency queries …. ホットプレート (Hot Plate) … タジン鍋 (Tagines) Already existing in Rakuten Category Tree No responding genre Create new category (a couple of years ago) You can find “タジン鍋” without using search 15
- 16. Types of queries Needs browsing function for not only category tree but also other attributes Ratio of Query Types Podcut Category Brand Merchant Spec Character Others Source: User Queries tat Rakuten Ichiba in 2013 16
- 17. Master Database Create new master database for brand, color and so on Data Structure behind Navigation Data Source Master Data Already Exist Brand Master. a Category Tree Navigation Category ….. ….. ….. Brand Brand Master. b Brand Master. c Integration Unified Brand Master New Color Master … ….. ….. ….. Color ….. ….. ….. New 17
- 18. 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 http://www.kalita.co.jp/ • The Same Thing with Different Names • Samsung • サムスン http://www.carita.jp/ 18
- 19. 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 - … Result check 19
- 20. Check by hand with few costs OpenRefine is very helpful Server side Original Matching Algorithm API for Open Refine Web Interface ID Name Useful Open Source Tool Other Master Data xxx SONY SONY [ Matched ] yyy カリタ Karita [ Candidate1 ] CARITA [ Candidate 2] …. …. http://openrefine.org 20 source http://www.carita.jp/
- 21. Color Master Building color dictionary automatically as much as possible Color Dictionary 16 color groups 1,871 color names 黒 Black 黒色 . . blac k Blue . . . • Image Processing • Natural Language Processing blue navy 21
- 22. Tagging Data for each item Structured Data Category Brand Color …. Merchant Input Item ID Category Brand Color … Extract Automatically From item description (in research) xxxx 22
- 23. Attribute value extraction • Generate extraction rules using attribute value database constructed from table data Table data Chateau d’Issan 1994 Database : <Region, Margaux> <Color, White> : This is a wine from Margaux. ... Rule wine from x => x is a Region Values not included in the database can be captured. Annotation Item page including a dictionary entry 23
- 24. Measurement/Modification Modification on WEB-tool Drag and Drop Easy to modify!! 24
- 26. Extra Measurement/Modification Old modification style Problem Achieved limit counts by excel orz … 26
- 27. Measurement/Modification Good Categorize = A huge benefit Very Important phase Need to survey trend and data optimization 27
- 30. Release Need it more rapidly!! Measurements Modification Release 30
- 31. Extra - Before Release Hard to release Category data Category data has over 15 DB… Deliver its data to all 50 service. Have over 15 DB.... RMS GMS Report TOP page Search Engine Rakuten Search Web Service Deliver data to all service Add new service sometime Advertisement Auction Review Books Racoupon kobo Auto Browsing History Super DB Affiliate Ranking Basket Mail Item Page 31
- 32. Extra - Before Release Show the Maintenance time table When Category Restructuring maintenance. Related Category Restructuring task Complicated!!! is almost 300 !! 32
- 33. Release Easy to release by all service more speedy Already Automation In Progress for Automation ServiceA Category Data API Now improving! ServiceB ServiceC ServiceD ServiceE ・・ ・・ 33
- 34. Release ■System Reconstruction used by API Before 6month Making data by handmade Share data by dump or excel In Progress Making data by management tool Reflect new Data used by API API Test and operate by each service ServiceA serviceB serviceD serviceE serviceC ・・ ・・ Every week Category Data serviceB serviceD Release in Regular Maintenance ServiceA serviceE serviceC ・・ ・・ Release in week 34
- 35. Release More easily more Speedy!! For operation free Get rid of dependency in each service GMS Report RMS TOP page Search Engine Rakuten Search Web Service Advertisement Category API Auction Books Review Racoupon Category Data kobo Auto Browsing History Super DB Affiliate Ranking Basket Mail Item Page 35
- 36. Release ■Real Time reflection Can be released Category Data and search it by “Real Time” on Real Time reference iPhone5s Rakuten Search. Register Real Time released when needed. 36
- 37. Release ■Real Time reflection Can be released Category Data and summarize it on Ranking. Register iPhone5s Released as a daily/weekly Ranking data. 37
- 38. Release ■Real Time reflection Can be released Category Data and Create Landing-page. Register iPhone5s Can be created Landing-page used by new Categorydata 38
- 39. Finally Standardization for cycle of Improvement Measurements Modification Release 39
- 40. Finally Benefit!! Category User Come across items optimization is Shop Sell items made everyone Rakuten Sell items Data analysis happy!! 40
- 41. Finally Thank you for your Listening!! If you have any idea or question, Please contact us. Let’s talk about Category with us!! Suguru Suzuki Yuhei Nishioka @sugsuzuki @nishiokamegane sugru.suzuki @mail.rakuten.com yuhei.nishioka @mail.rakuten.com 41