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Web Intelligence Introduction


Next paradigm shift in the Web WEB INTELLIGENCE ... ends and the best means; discernment and judgment; discretion; sagacity; skill; dexterity ... – PowerPoint PPT presentation

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Title: Web Intelligence Introduction

Web IntelligenceIntroduction
  • Introduction
  • The Wisdom We
  • Levels of WI vs. Social Intelligence
  • Extensional Description of WI

  • Popularity of Web
  • Web revolutionize the way in which information is
    gathered, stored, processed, presented, shared,
    and used
  • Next paradigm shift in the Web ? WEB INTELLIGENCE
  • WI is a new direction for scientific research and
    development that explores the fundamental roles
    as well as practical impacts of AI and advanced
    IT on the next generation of Web-empowered
    products, systems, services, and activities
  • WI is a new paradigm for developing the Wisdom
    Web and Web-supported social network intelligence

The Wisdom Web
  • The next paradigm shift in WWW will lie in the
    keyword of wisdom
  • The new generation of WWW will enable users to
    gain new wisdom of living, working, playing, and
    learning, in addition to information search and
    knowledge queries
  • Wisdom
  • The quality of being wise knowledge, and the
    capacity to make due use of it knowledge of the
    best ends and the best means discernment and
    judgment discretion sagacity skill dexterity
  • The results of wise judgment scientific or
    practical truth acquired knowledge erudtion

A Minimalist Wisdom Web Scenario
  • Day 1
  • You log on to the Wisdom Web as a user
  • You What is the best night life in Montreal
    during this season of the year?
  • WW The hockey games are on during this season
    of the year. Would you like to go?
  • You Yes
  • WW There are still some tickets left and you
    may purchase some at the Montreal Forum. To get
    there, you need to take Metro and get off at the
    Atwater station.
  • ? the tickets are all for the day after tomorrow

A Minimalist Wisdom Web Scenario (Cont.)
  • Day 2
  • You log on to the Wisdom Web as a user
  • WW Hi Spiderman, you were in such a hurry
    yesterday that I did not have a chance to tell
    you that the tickets available are only for
    tomorrow and they are quite expensive too.

Fundamental Capabilities of the Wisdom Web
  • Autonomic Web support the Web automatically
    regulates the functions and cooperation of
    related Websites and application services
  • Reflex of servers A Wisdom Web server must be
    able to automatically self-nominate to other
    services its functional roles as well as
    corresponding spatial or temporal constraints and
    operational settings.
  • Specialization A Wisdom Web server has to be an
    agent by itself that is specialized in performing
    some roles in a certain service. The association
    of its roles with any service will be measured
    and updated dynamically.
  • Growth The population of the WisdomWeb agents
    will dynamically change, as new agents are
    self-reproduced by their parent agents in order
    to become more specialized or aged agents are

Fundamental Capabilities of the Wisdom Web (Cont.)
  • Autonomic Web support
  • Auto-catalysis As various roles of the Wisdom
    Web agents are created through specialization and
    activated by the Wisdom Search requests, their
    associations with some services and among
    themselves must be auto-catalytically aggregated.
    In this respect, the auto-catalysis of
    associations is similar to the pheromone laying
    for positive feedback in an ant colony.
  • Problem Solver Markup Language (PSML) PSML is
    necessary for the Wisdom Web agents to specify
    their roles and settings as well as relationships
    with any other services. The core of PSML is an
    inference engine that can do automatic reasoning
    on the Web by incorporating the content and
    meta-knowledge automatically collected and
    transformed from the Web with locally operational

Fundamental Capabilities of the Wisdom Web (Cont.)
  • Semantics The Wisdom Web needs to understand
    what are meant by Montreal, season, year,
    and night life, and what is the right judgment
    of best, by understanding the granularities of
    their corresponding subjects and the whereabouts
    of their ontology definitions.
  • Meta-knowledge Besides semantic knowledge
    extracted and manipulated in the Wisdom Search,
    it is also essential for the Wisdom Web agents to
    incorporate a dynamically created source of
    meta-knowledge that deals with the relationships
    between concepts and the spatial or temporal
    constraint knowledge in planning and executing
    services. It allows the agents to self-resolve
    their conflict of interests.

Fundamental Capabilities of the Wisdom Web (Cont.)
  • Planning In the above example, the goal is to
    find a function or an event that may sound
    attractive to a visitor. The constraint is that
    they must be happening during this season. There
    are involved two associated sub-goals In order
    to have an access to the recommended function or
    event, one needs a ticket. Further, in order to
    go to get the ticket, one can travel by Metro. In
    the Wisdom Web, ontology alone will not be
  • Personalization The Wisdom Web remembers the
    recent encounters and relates different episodes
    together, according to (1) Spiderman, (2) time,
    and (3) attainability of (sub-)goals. It may
    further identify other goals as well as course of
    actions for this user as their conversation goes

Fundamental Capabilities of the Wisdom Web (Cont.)
  • A sense of humor Although the Wisdom Web does
    not explicitly tell a funny story, it adds some
    punch lines to the situation or anxiety that
    Spiderman is presently in when he logs on for
    the second time, which will make Spiderman feel

Fundamental Capabilities of the Wisdom Web (Cont.)
  • The semantics contributes one aspect of WI
  • We expect the Web not just to extend the
    knowledge of artificial assistants, but to extend
    their intelligence
  • Developing the Wisdom Web is an important goal
    for WI research

Levels of WI vs. Social Intelligence
Levels of WI
Application-level ubiquitous computing and
social intelligence utilities
Knowledge-level information processing and
management tools
Semantic Web
Interface-level multi-media presentationstandards
Internet-level communications, infrastructure,
and security protocols
Support functions
Conceptual Levels of WI
  • Internet-level communication, infrastructure, and
    security protocol
  • The Web is regarded as a computer-network system
  • Web data pre-fetching systems
  • Adaptive learning process based on observation of
    user surfing behavior
  • Interface-level multimedia presentation standards
  • The Web is regarded as an interface for
    human-Internet interaction
  • Intelligent Web interfaces
  • Adaptive cross-language processing, personalized
    multimedia representation, and multi-modal data

Conceptual Levels of WI (Cont.)
  • Knowledge-level information processing and
    management tools
  • The Web is regarded as a distributed
    data/knowledge base
  • Develop semantic markup languages to represent
    the semantic contents of the Web available in
    machine-understandable formats for agent-based
    autonomic computing such as searching,
    aggregation, classification, filtering, managing,
    mining, and discovery on the Web

Conceptual Levels of WI (Cont.)
  • Application-level ubiquitous computing and social
    intelligence environments
  • The Web is regarded as a basis for establishing
    social networks that contain communities of
    people (or organizations or other social
    entities) connected by social relationship, such
    as friendship, co-working or information exchange
    with common interests. (Web-supported social
    networks or virtual communities)
  • Social network intelligence (or just social
  • Mobile platform
  • Ubiquitous Web access and computing from various
    wireless devices needs adaptive personalization
    for which WI techniques are used to construct
    models of user interests by inferring implicitly
    from user behavior and actions

Social Network Intelligence for Enterprise Portals
  • One of the most sophisticated applications on the
    Web today is enterprise information portals
  • Search, retrieve, and repackage data with markup
  • WI researchers need to study both centralized and
    distributed information structures
  • Centralized via intelligent portal uniformity
    and access
  • Distributed combinatory complexity
  • Use PSML for collecting globally distributed
    contents and knowledge from Web-supported social
    networks and incorporating them with locally
    operational knowledge/databases in an enterprise
    or community for local centralized, adaptable Web
    intelligence services

Social Network Intelligence for Enterprise
Portals (Cont.)
  • Social network
  • A self-organizing structure of users,
    information, and communities of expertise
  • Play a crucial role in implementing
    next-generation enterprise portals with functions
    such as data mining and knowledge management for
    discovery, analysis , and management of social
    networks knowledge
  • Placed at the top of a four-level WI
  • Supported by functions including security,
    prefetching, adaptive cross-language processing,
    personalized multimedia representation, semantic
    searching, aggregation, classification,
    filtering, managing, mining, and discovery

Extensional Description of WI
  • WI in an enhancement of an extension of AI and IT
  • WI may be viewed as applying results from
    existing disciples of AI and IT to a totally new
  • WI may also be expected to introduce new problems
    and challenges to established disciplines

An Intelligent Web-based Business-centric
Schematic Diagram of WI-related Topics
Intelligent Web-Based Business
  • Business Intelligence
  • Customer Relationship Management
  • Electronic Commerce and Electronic Business
  • Measuring and Analyzing Web Merchandising
  • Price Dynamics and Pricing Algorithms
  • Targeted Marketing
  • Web-Based EDI
  • Web Marketing
  • Web Publishing
  • Web Services

Knowledge Networks and Management
  • Electronic Library
  • Information and Knowledge Markets
  • Network Community Formation and Support
  • Ontology Engineering
  • Semantic Web
  • Visualization of Information and Knowledge
  • Web-based Decision Support
  • Web Regularities and Models

Ubiquitous Computing and Social Intelligence
  • Competitive Dynamics of Web Sites
  • Computational Societies and Markets
  • Dynamics of Information Sources
  • Reputation Mechanisms
  • Social Networks
  • Theories of the Small-World Web
  • Ubiquitous Learning Systems
  • Ubiquitous Web Access
  • Web-Based Cooperative Work
  • Web Security, Integrity, Privacy and Trust
  • Wireless Web Intelligence

Intelligent Human-Web Interaction
  • Adaptive Web Interfaces
  • Multimodal Data Processing
  • Multimedia Representation
  • Science and Art of Web Design

Web Information Management
  • Data Models for the Web
  • Internet and Web-Based Data Management
  • Multi-Dimensional Web Databases and OLAP
  • Multimedia Information Management
  • Object-Oriented Web Information Management
  • Personalized Information Management
  • Use and management of Metadata
  • Web-Based Distributed Information Systems

Web Information Retrieval
  • Automatic Cataloging and Indexing
  • Conceptual Information Extraction
  • Multimodal Information Retrieval
  • Multilinguistic Information Retrieval
  • Multimedia Retrieval
  • Ontology-Based Information Retrieval
  • Information Retrieval Support Systems

Web Agents
  • Conversation Systems
  • E-mail Filtering and Automatic Handling
  • Global Information Foraging
  • Information Filtering
  • Navigation Guides
  • Recommender Systems
  • Resource Intermediary and Coordination Mechanisms
  • Remembrance Agents
  • Semantic Web Agents

Web Mining and Farming
  • Data Mining and Knowledge Discovery for WI
  • Learning User Profiles
  • Multimedia Data Mining
  • Text Mining
  • Web-Based Ontology Learning
  • Web-Based Reverse Engineering
  • Web Farming
  • Text Categorization
  • Web-Content Mining, Web-Log Mining, Web-Structure
  • Web Warehousing

Emerging Web Technology and Infrastructure
  • Grid Computing
  • New Web Information Description and Query
  • Peer-to-Peer Computing
  • Problem Solver Markup Language (PSML)
  • Soft Computing (including neural networks, fuzzy
    logic, evolutionary computation, rough sets, and
    granular computing) and Uncertainty Management
    for WI
  • Web Document Prefetching
  • Web Inference Engine
  • Web Intelligence Development Tools
  • Web Protocols
  • Wisdom Web

Course Outline
  • Semantic Web
  • Understanding XML and its impact on the Semantic
  • Understanding Web Services
  • Understanding RDF and RDF Schema
  • Understanding Taxonomies and Topic Map
  • Understanding Ontologies and DAMLOIL
  • Web Intelligence
  • Web Mining and Farming
  • Web Information Retrieval
  • Web Knowledge Management
  • Web Agents
  • Infrastructure for Web Intelligent Systems
  • Social Network Intelligence
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