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Self Introduction

Date post: 15-Jul-2015
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http://degulab.cs.dis.titech.ac.jp/~umeda07/ Deguchi Lab. Self-Introduction name Takashi UMEDA biography 1985 born in gifu pref. 2003~2007 Faculty of Informatics, Shizuoka Univ. 2007~2009 Deguchi Lab, Dep.of Computational Intelligence and Systems Science, Tokyo Institute Of Techology Research Interest Recommendation algorithms, Information diffusion on the Internet, Consumer behavior on EC, Bachelor’s thesis The research into direct financing in Silicon Valley by Agent Based Modeling master's thesis Evaluation of Collaborative Filtering by Agent-Based Simulation in the light of a market environment URL http://degulab.cs.dis.titech.ac.jp/~umeda07/ 1
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http://degulab.cs.dis.titech.ac.jp/~umeda07/Deguchi Lab.

Self-Introduction

name Takashi UMEDA

biography 1985 born in gifu pref.

2003~2007 Faculty of Informatics, Shizuoka Univ.

2007~2009 Deguchi Lab, Dep.of Computational

Intelligence and Systems Science, Tokyo Institute

Of Techology

Research Interest Recommendation algorithms,

Information diffusion on the Internet,

Consumer behavior on EC,

Bachelor’s thesis The research into direct financing in Silicon Valley

by Agent Based Modeling

master's thesis Evaluation of Collaborative Filtering by Agent-Based

Simulation in the light of a market environment

URL http://degulab.cs.dis.titech.ac.jp/~umeda07/

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http://degulab.cs.dis.titech.ac.jp/~umeda07/Deguchi Lab.

Research Interest1/3 (Objective)

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– なぜ協調フィルタリングか?:

• 最もポピュラー

• 特にユーザベース手法に焦点

– なぜABSか?: • 市場構造を考慮可能

– 分析内容:• ネイバー数と市場構造の関係

• ネイバー数:パラメータの1つ

Evaluating and designing the recommendation algorithm on EC in the light of the market environments

It is able to give some useful knowledge about the recommendation for people who are engaged in web marketing, web system or EC business.

Recommendation: Collaborative Filtering

• Amazon.com• user base CF

Method: ABS• It is possible to model the interaction with market environment and recommendation

Objectives

http://degulab.cs.dis.titech.ac.jp/~umeda07/Deguchi Lab.

Research Interest 2/3 (model)

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EC Site• item-1(category1)• item-2(category2)• item-3(category3)

consumer

consumer

consumer

buy

recommend

buy

recommend

buy

recommend

Consumer model

Each consumer has some

parameters that are used to decide

what he buys.

Recommendation model

Collaborative Filtering(k-nearest neighbor )

Each item sold in the EC Website belongs to one category

http://degulab.cs.dis.titech.ac.jp/~umeda07/Deguchi Lab.

Resarch Interest 3/3(Implement)

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SOARS(.vml) Consumer’s decision making

Collaborative Filtering

Consumer Agent

EC Spot

Consumer’s preference

Item’s attribute

External Object (.Java)Data File (.CSV)

Sinario

Result

Execute! The simulation is executed on the Grid machines.

http://degulab.cs.dis.titech.ac.jp/~umeda07/Deguchi Lab.

Research Interest 4/4(Conclusion)

I’m performing the experiments very hard now!

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