Web Intelligence Introduction

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Web IntelligenceIntroduction
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Outline

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

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Introduction

• 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

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The Wisdom Web
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Overview

• 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

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A Minimalist Wisdom Web Scenario

• Day 1
• You log on to the Wisdom Web as a user
  Spiderman
• 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

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A Minimalist Wisdom Web Scenario (Cont.)

• Day 2
• You log on to the Wisdom Web as a user
  Spiderman
• 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.

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Fundamental Capabilities of the Wisdom Web

• Autonomic Web support the Web automatically
  regulates the functions and cooperation of
  related Websites and application services
  available.
• 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
  deactivated.

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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
  knowledge/databases.

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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.

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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
  sufficient.
• 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
  on.

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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
  absurd.

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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

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Levels of WI vs. Social Intelligence
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Levels of WI
Application
Application-level ubiquitous computing and
social intelligence utilities
Level-4
Knowledge-level information processing and
management tools
Level-3
Semantic Web
Interface-level multi-media presentationstandards
Level-2
Internet-level communications, infrastructure,
and security protocols
Level-1
Support functions
Hardware
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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
  processing

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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
• THE SEMANTIC WEB

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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
  intelligence)
• 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

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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
  languages
• 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

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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
  infrastructure
• Supported by functions including security,
  prefetching, adaptive cross-language processing,
  personalized multimedia representation, semantic
  searching, aggregation, classification,
  filtering, managing, mining, and discovery

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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
  domain
• WI may also be expected to introduce new problems
  and challenges to established disciplines

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An Intelligent Web-based Business-centric
Schematic Diagram of WI-related Topics
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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

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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

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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

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Intelligent Human-Web Interaction

• Adaptive Web Interfaces
• Multimodal Data Processing
• Multimedia Representation
• Science and Art of Web Design

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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

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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

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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

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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
  Mining
• Web Warehousing

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Emerging Web Technology and Infrastructure

• Grid Computing
• New Web Information Description and Query
  Languages
• 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

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Course Outline

• Semantic Web
• Understanding XML and its impact on the Semantic
  Web
• 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