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Computational Web Intelligence for Wired and Wireless Applications

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Title: Computational Web Intelligence for Wired and Wireless Applications


1
Computational Web Intelligence for Wired and
Wireless Applications
  • Yan-Qing Zhang
  • Department of Computer Science
  • Georgia State University
  • Atlanta, GA 30302-4110
    yzhang_at_cs.gsu.edu

2
Outline
  • Introduction
  • Computational Intelligence
  • Web Technology
  • Computational Web Intelligence (CWI)
  • Wired and Wireless Applications
  • Conclusion and Future Work

3
Introduction
  • QoI (Quality of Intelligence) of e-Business
  • WI AI IT
  • WI (Web Intelligence) exploits Artificial
    Intelligence (AI) and advanced Information
    Technology (IT) on the Web and Internet .
  • (Zhong, Liu, Yao and Ohsuga) at Proc. the 24th
    IEEE Computer Society International Computer
    Software and Applications Conference (COMPSAC
    2000),

4
Introduction (cont.)
  • CI is a subset of AI,
  • CI is not a subset of AI, there is an overlap
    between AI and CI.
  • In general, CI?AI.
  • crisp logic and rules in AI, and fuzzy logic and
    rules in CI (Zadeh).
  • Motivation Input CI onto Web?

5
Computational Intelligence
  • fuzzy computing (FC)
  • neural computing (NC),
  • evolutionary computing (EC),
  • probabilistic computing (PC),
  • granular computing (GrC)
  • rough computing (RC).

6
Web Technology
  • a hybrid technology including computer networks,
    the Internet, wireless networks, databases,
    search engines, client-server, programming
    languages, Web-based software, security, agents,
    e-business systems, and other relevant
    techniques.

7
Computational Web Intelligence (Zhang and Lin,
2002)
  • Uncertainty on the Web (FLINT 2001 at BISC at UC
    Berkeley http//www-bisc.cs.berkeley.edu/)
    (Zhang, et al, 2001 (a), (b) (c))
  • CWI CI WT (Zhang and Lin, 2002)
  • CWI is a hybrid technology of Computational
    Intelligence (CI) and Web Technology (WT) on
    wired and wireless networks.
  • CWI is dedicating to increasing QoI of
    e-Business applications with uncertain data on
    the Internet and wireless networks.

8
Computational Web Intelligence (cont.) (Zhang and
Lin 2002)
  • Fuzzy Web Intelligence
  • Neural Web Intelligence
  • Evolutionary Web Intelligence
  • Probabilistic Web Intelligence
  • Granular Web Intelligence
  • Rough Web Intelligence
  • Hybrid Web Intelligence

9
(No Transcript)
10
  • Preface. . . . . . . . . . . . . . . . . . . . .
    . . . . v
  • Introduction to Computational Web Intelligence
    and Hybrid Web Intelligence. . .. . . . . . . . .
    . . . . xviii
  • Part I Fuzzy Web Intelligence, Rough Web
    Intelligence and Probabilistic Web Intelligence.
    . . . ... . . . . . . . . . . . . . . . . . . 1
  • Chapter 1. Recommender Systems Based on
    Representations. .. . . 3
  • Chapter 2. Web Intelligence Concept-based Web
    Search. . . . . . . 19
  • Chapter 3. A Fuzzy Logic Approach to Answer
    Retrieval from the World-Wide-Web .. . . . . . .
    . . . . . . . . . . . . . . . . . . . . . . . 53
  • Chapter 4. Fuzzy Inference Based Server
    Selection in Content Distribution Networks. . . .
    . . . . . .. . . . . . . . . . . . . . . . . . .
    . . . 77
  • Chapter 5. Recommendation Based on Personal
    Preference. . . ..101
  • Chapter 6. Fuzzy Clustering and Intelligent
    Search for a Web-based Fabric Database. . . . . .
    . . . . . . . . . . . . . . . . . . . . . . . . .
    . . . . . 117
  • Chapter 7. Web Usage Mining Comparison of
    Conventional, Fuzzy and Rough Set Clustering . .
    . . . . .. . . . . . . . . . . . . . . . . . . .
    . . . . . . 133
  • Chapter 8. Towards Web Search Using Contextual
  • Probabilistic Independencies. . . . .. . . . . .
    . . . . . . . . . .. . . . . . . 149

11
  • Part II Neural Web Intelligence, Evolutionary
    Web Intelligence and Granular Web
    Intelligence 167
  •  
  • Chapter 9. Neural Expert System for Vehicle
    Fault Diagnosis
  • via The WWW. . . .. . . . . . . . .. . . . . . .
    . . . . . . . . . . . . . . . . .169
  • Chapter 10. Dynamic Documents in The Wired
    World.. ... . . . .183
  • Chapter 11. Proximity-based Supervision for
    Flexible
  • Web Page Categorization. . . . .. . . . . . .. .
    . . .. . . . . . . . . . 205
  • Chapter 12. Web Usage Mining Business
    Intelligence From Web Logs. . . . 229
  • Chapter 13. Intelligent Content-Based Audio
    Classification and Retrieval for Web Application.
    . . . . . . . . . . . . . . . . . . . . . . . . .
    . 257
  •  

12
  • Part III Hybrid Web Intelligence and
    e-Applications 283
  • Chapter 14. Developing an Intelligent
    Multi-Regional Chinese Medical Portal. . . . . .
    . . . . . . . . . . . . . . . . . . . . . . . . .
    . . . .285
  • Chapter 15. Multiplicative Adaptive User
    Preference Retrieval and Its Applications to Web
    Search. . . . . . . . . . . . . . . . . . . . . .
    . . . . . . .303
  • Chapter 16. Scalable Learning Method to Extract
    Biological Information from Huge Online
    Biomedical Literature. . . . . . . . . . . . . .
    . . . . .329
  • Chapter 17. iMASS An Intelligent
    Multi-resolution Agent-based Surveillance System.
    . . . . . . . . . . . . . . . . . . . . . . . . .
    . . . . . . . .347
  • Chapter 18. Networking Support for Neural
    Network-based Web Monitoring and Filtering. . . .
    . . . . . . . . . . . . . . . . . . . . . . . . .
    . . 369
  • Chapter 19. Web Intelligence Web-based BISC
    Decision Support System (WBICS-DSS) . . . . . . .
    . . . . . . . . . . . . . .. . . . . . . . . . .
    .391
  • Chapter 20. Content and Link Structure Analysis
    for Searching the Web. 431
  • Chapter 21. Mobile Agent Technology for Web
    Applications. . . . 453
  • Chapter 22. Intelligent Virtual Agents and the
    WEB. . . . . . . . . . .481
  • Chapter 23. Data Mining in Network Security. . .
    . . . . . . . . . . . . .501
  • Chapter 24. Agent-supported WI Infrastructure
    Case Studies in Peer-to-peer Networks. . . . . .
    . . . . . . . . . . . . . . . . . . . . . . . . .
    . . . . 515
  • Chapter 25. Intelligent Technology for Content
    Monitoring on the Web. .539

13
Wired and Wireless Applications
  • CWI has various applications in intelligent
    e-Business on the Internet and on wireless mobile
    networks.
  • 1. Neural-Net-based online Stock Agents,
  • 2. Personalized Mobile Phone Agents,
  • 3. Mobile Wireless Shopping Agents,
  • 4. Mobile Wireless Fleet Application (Yamacraw
    Research Project).

14
Fuzzy Neural Web Agents for Stock Prediction
(Zhang, et al, 2001)
  •  

 To implement this stock prediction system, Java
Servlets, Java Script and Jdbc are used. SQL is
used as the back-end database.
15
Fig 1. Graph of Predicted and Real values for
dow stock using complete data (Zhang, et al,
2001)
16
Personalized Wireless Information Agents for
Mobile Phones
17
Personalized Weather Agent
18
  • Mobile Wireless Shopping Agents

19
Mobile Fleet Application(Yamacraw Research
Project)
  • Automated scheduling of pickups and deliveries
  • Distributed design
  • Emergency Handling
  • On-the-fly scheduling of package exchanges
    between trucks (rendezvous peer-to-peer
    interaction)
  • Demo

20
(No Transcript)
21
Truck to Truck Communication
  • A truck (Truck1) sends a request to the SyD
    Listener on a peer truck using SyD Engine
    invoke method.
  • A selected (Truck2) peer resolves the request
    using Its own SyD Listener and Engine.
  • Sends the result back to the calling peer
    (Truck1).
  • IP address of peers are resolved using the SyD
    directory service running in a central location
  • Each device is capable of functioning as client
    or server.

SyD listener
SyD Listener
Truck AppO
Truck AppO
SyD Engine
SyD Engine
TDB
TDB
DBS Database service TDB Truck database
Truck1
Truck2
22
Conclusion
  • CWI based on CI and WT, a new research area, is
    proposed to increase the QoI of e-Business
    applications.
  • CWI has a lot of wired and wireless applications
    in intelligent e-Business. FWI, NWI, EWI, PWI,
    GWI, RWI, and HWI are major CWI techniques
    currently.

23
Future Work
  • CWI on wired and mobile wireless networks.
  • Web Data Mining and Knowledge Discovery.
  • Intelligent wireless mobile PDAs (do smart
    e-Business, Homeland Security, etc.)
  • Intelligent Wireless Mobile Agents (in cars,
    houses, offices, etc.)
  • Intelligent Bioinformatics on the Web
  • CWI and Grid Computing.

24
References
  • 1 Y.-Q. Zhang, A. Kandel, T.Y. Lin and Y.Y. Yao
    (eds.), Computational Web Intelligence
    Intelligent Technology for Web Applications,
    Series in Machine Perception and Artificial
    Intelligence, volume 58, World Scientific, 2004.
  • 2 Y.-Q. Zhang and T.Y. Lin, Computational Web
    Intelligence (CWI) Synergy of Computational
    Intelligence and Web Technology, Proc. of
    FUZZ-IEEE2002 of World Congress on Computational
    Intelligence 2002 Special Session on
    Computational Web Intelligence, pp. 1104-1107,
    Honolulu, May 2002.
  • 3 M. Atlas and Y.-Q. Zhang, Fuzzy Neural Web
    Agents for Efficient NBA Scouting, Web
    Intelligence and Agent Systems An International
    Journal, vol. 6, no. 1, pp. 83-91, 2008.
  • 4 Y.-Q.  Zhang, S. Hang, T.Y. Lin and Y.Y. Yao,
    Granular Fuzzy Web Search Agents, Proc. of
    FLINT2001, pp. 95-100, UC Berkeley, Aug. 14-18,
    2001.
  • 5 Y.-Q. Zhang, S. Akkaladevi, G. Vachtsevanos
    and T.Y. Lin,  Fuzzy Neural Web Agents for Stock
    Prediction, Proc. of FLINT2001, pp. 101-105, UC
    Berkeley, Aug. 14-18, 2001.
  • 6 Y. Tang and Y.-Q. Zhang, Personalized
    Library Search Agents Using Data Mining
    Techniques, Proc. of FLINT2001, pp. 119-124, UC
    Berkeley, Aug. 14-18, 2001.

25
Thank you!
  • Any Question?
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