Stephen Wang http://stephenwang.com Alivenotdead.com CTO mongoDB Beijing Presentation (March 3, 2011)： From Rotten Tomatoes to alivenotdead.com to alive.cn, an explanation of the evolution of building an entertainment database at each stage of evolution. The current version is a multi-lingual global entertainment database using linked open data and mongoDB.

1. Building a super database from linked data
Stephen Wang 王傳仁
me@stephenwang.com
March 3, 2011

2. Who is this NOT for?
Who IS this for?

Building a large database from a tiny team

Organizing the world's information

Information innovation

3. About

Co-founder, CTO

Popular movie reviews web site

Aggregated reviews,
comprehensive film database

4. The Stone Age

Static HTML
templates

Editors read articles
and pull quotations

Only cover the
newest movies

~1000 films

5. Modern Times

Shift to LAMP

License long-tail
database

Automated spiders,
early UGC via critics
(How I felt maintaining Rotten

Use homegrown
Tomatoes' overloaded database servers) CMS for additional
content

6. v
The Result

8 million unique visitors / month

Lean startup: 25x traffic with 7 staff

Great site for film lovers (including Steve Jobs)

7. About

Co-founder, CTO

SNS for artists started
with Daniel Wu 吴彦祖

Started with six artists,
now 1,600 artists,
600K registered users

Also powers official
web sites:
李连杰： JetLi.com
成龙： JackieChan.com
莫文蔚： KarenMok.com

8. Our LAMP stack: Not the best setup for...
Newsfeeds...
Viral loop analysis...
Multivariate testing...
The Problem?!?
Scalability issues with real-time data, but without traffic from
public, long-tail content

9. About

A better
entertainment
database

Providing the long-
tail content

Still a part of
alivenotdead.com

Still in alpha

10. Features

Comprehensive info
for celebrities, films,
music, and TV

Searchable, structured
data

Multilingual: English,
Chinese, Japanese

Aggregated social
media from
inside/outside China

11. Why use mongoDB?
Flexible schema for different data sources
Dozens of other sources...

12. Why use
Scalable big data

2 million+ topics 
500,000 translations
covered
Next challenge:
Aggregating and
storing the social
media firehose

13. Why use
Crossing the border...

Alivenotdead.com 
alive.tom.com in
in Hong Kong Tianjin
Use replica sets/eventual consistency to overcome
frequent cross-border network issues

14. Using Linked Open Data

Wikipedia as structured data

Creative Commons license

Multiple CC sources

Organized taxonomy

Acquired by Google

No Chinese/Japanese yet!

15. Using Linked Open Data

Wikipedia as structured data

Creative Commons license

Only Wikipedia

Messy taxonomy

Chinese/Japanese topic
translations, but requires
English topic link

16. Using Linked Open Data

Use Freebase organized taxonomy, broad data

Expand DBpedia to Chinese-only topics

Same methodology across Chinese wiki sources

17. The Future

Developer API

Topic extraction

Real-time trends
across languages

Other verticals
Already 10x more data than Rotten Tomatoes...
The complete sum of information from across the web...
Information not constrained by language...

18. We're hiring PHP engineers! Send your CV to
me@stephenwang.com
My blog: http://stephenwang.com