Fuzzy Mobile Agents for Distributed e-Shopping Data Mining

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Fuzzy Mobile Agents for Distributed e-Shopping
Data Mining

• Presented by
• Lin Lu

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Acknowledgement

• First of all, thanks to Dr. Zhang for guidance,
  encouragement and patience throughout the length
  of the project
• Thanks also go to my committee member, Dr.
  Sunderraman, for his continuous support over the
  time of my stay at GSU

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Overview

• Introduction
• Architecture of KAARIBOGA Mobile Agents
• Design Issues of FMADeSDM
• Implementations of FMADeSDM
• Concluding Remarks
• Demo

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Introduction

• Background and purpose
• Explosive growth of World Wide Web (WWW) makes
  retrieving information of interest dramatically
  more challenging
• Currently-used smart commercial search engines
  always fall short in providing prompt and
  efficient results
• Mobile agent paradigm has been recently
  developed, with high demands in e-commerce
  applications
• Demands for Intelligent mobile agent

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Introduction

• What is mobile agent?
• A mobile agent is an autonomous program that
  can migrate through a heterogeneous network
  searching for and interacting with services on
  user's behalf.

• What is fuzzy logic?
• Fuzzy logic is a superset of conventional
  (Boolean) logic that has been extended to handle
  the concept of partial truth -- truth values
  between "completely true" and "completely false".

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Introduction (cont.)

• Why fuzzy logic?
• Fuzzy logic uses soft linguistic variables to
  represent the range of numerical values and allow
  these linguistic values to overlap.
• Fuzzy logic can be used to deal with uncertain
  information to come up with decisions, which is
  ideal for solving real-world problems.

• Algorithms used in the project
• Fuzzy-user-preference-based ranking algorithm
• Distributed data mining algorithm and centralized
  data-mining algorithm

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Architecture of KAARIBOGA Mobile Agents

• Life-cycle Model

Creation Start Destroy Dispatch
Arrival Sleep Awake Message
handling
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Architecture of KAARIBOGA Mobile Agents (cont.)

• Navigation Model

Transfer agent between Kaariboga bases
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Architecture of KAARIBOGA Mobile Agents (cont.)

• Communication Model

Message exchange between agents and/or bases
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Architecture of KAARIBOGA Mobile Agents (cont.)

• Architecture of Kaariboga System

Architecture of Kaariboga system
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Design Issues of FMADeSDM

• Fuzzy Ranking

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Design Issues of FMADeSDM(cont.)

• Fuzzy Ranking Example

Rank
0.64
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Design Issues of FMADeSDM(cont.)

• Shopping Searching Agents
• Search Agent 1

Scenario for search agent 1
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Design Issues of FMADeSDM(cont.)

• Shopping Searching Agents
• Search Agent 2

Scenario for search agent 2
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Design Issues of FMADeSDM(cont.)

• Shopping Searching Agents
• Search Agent 3

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Implementation of FMADeSDM

• Fuzzy Ranking

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Implementation of FMADeSDM(cont.)

• Search Agent 1

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Implementation of FMADeSDM(cont.)

• Search Agent 2 3

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Concluding Remarks

• Kaariboga Mobile Agents system is introduced and
  studied
• Fuzzy Mobile Agents for Distributed e-Shopping
  Data Mining System is developed
• Implemented three kinds of search mobile agents
• Proposed a simple scenario to monitor the
  aliveness of each search agent

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Concluding Remarks (cont.)

• Fuzzy-user-preference-based ranking algorithm is
  used
• Dynamically updated fuzzy values are employed in
  distributed data mining algorithm
• Ideas proposed in FMADeSDM can be extended to
  similar applications beyond the e-commerce
  application

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Demo