Intelligent Technologies for Web Applications

Intelligent Technologies for Web Applications

Συγγραφέας: Priti Srinivas Sajja, Rajendra Akerkar
ISBN: 9781439871621
Σελίδες: 367
Σχήμα: 18 X 26
Εξώφυλλο: Σκληρό
Έτος έκδοσης: 2012


The Internet has become an integral part of human life, yet the web still utilizes mundane interfaces to the physical world, which makes Internet operations somewhat mechanical, tedious, and less human-oriented. Filling a large void in the literature, Intelligent Technologies for Web Applications is one of the first books to focus on providing vital fundamental and advanced guidance in the area of Web intelligence for beginners and researchers.
The book covers techniques from diverse areas of research, including:
• Natural language processing
• Information extraction, retrieval, and filtering
• Knowledge representation and management
• Machine learning
• Databases
• Data, web, and text mining
• Human–computer interaction
• Semantic web technologies
To develop effective and intelligent web applications and services, it is critical to discover useful knowledge through analyzing large amounts of content, hidden content structures, or usage patterns of web data resources. Intended to improve and reinforce problem-solving methods in this area, this book delves into the hybridization of artificial intelligence (AI) and web technologies to help simplify complex Web operations. It introduces readers to the state-of-the art development of web intelligence techniques and teaches how to apply these techniques to develop the next generation of intelligent Web applications.
The book lays out presented projects, case studies, and innovative ideas, which readers can explore independently as standalone research projects. This material facilitates experimentation with the book’s content by including fundamental tools, research directions, practice questions, and additional reading.

Contents

Part I: Introduction to the Web, machine learning, new AI techniques, and web intelligence
Introduction to World Wide Web
Brief history of the Web and the Internet
Blogs
Tweets
Wikis
Collaborative mapping
Aggregation technologies
Open platforms, application programming interface, and programming tools
Web intelligence
Intelligence in web applications
Organization of this book
Machine learning concepts
Introduction
Linear regression
Supervised learning: Classification
Support vector machines
Nearest neighbor classifiers
Unsupervised learning: clustering
Hidden Markov models
Bayesian methods
Reinforcement learning
Applications of machine learning
Conclusion
Overview of constituents for the new artificial intelligence
Foundations of the new artificial intelligence and knowledge-based system
Fuzzy systems
Artificial neural networks
Genetic algorithms and evolutionary computing
Rough sets
Soft computing
Benefits of the new AI to World Wide Web
Web intelligence
Internet, web, grid, and cloud
Introduction to web intelligence
Perspectives of WI
Levels of WI
Goal of WI
Characteristics of web intelligence
Challenges and issues of WI
Wisdom web
Web-based support systems
Designing an intelligent web
Future of WI
Part II: Information retrieval, mining, and extraction of content from the Web
Web information retrieval
Introduction
Typical web search engines
Architecture of a web crawler
Distributed crawling
Focused spiders/crawlers
Collaborative crawling
Some tools and open source for web crawling
Information retrieval: beyond searching
Models of information retrieval
Performance measures in IR
Natural language processing in conjunction with IR
Knowledge-based system for information retrieval
Research trends
Conclusion
Web mining
Introduction to web mining
Evolution of web mining techniques
Process of web mining
Web content mining
Web usage mining
Web structure mining
Sensor web mining: architecture and applications
Web mining software
Opinion mining
Other applications using AI for web mining
Future research directions
Structured data extraction
Preliminaries
Wrapper induction
Locating data-rich pages
Systems for wrapper generation
Applications and commercial systems
Summary
Part III: Semantic web and web knowledge management
Semantic web
Introduction to semantic web
Metadata
Layered architecture of semantic web
Refined architecture of semantic web
Ontology and ontology constructs
Meta-ontology
Ontology tools and editors
Annotation tools
Inference engines
Semantic web applications
Semantic web interoperability and web mining
Semantic web and social communities
Semantic web and intelligent search
Semantic web research issues
Web knowledge management
About knowledge
Knowledge management fundamentals
Ontology revisited
Utilization of knowledge management methodologies on semantic web
Exchanging knowledge in virtual entities
Case study
Building the World Wide Why
Conclusion and applications
Social network intelligence
Introduction to social networking
Friend-of-a-friend
Semantically interlinked online communities
Social network analysis
Social network data
hCard and XFN
Advantages and disadvantages of social networking
Social graph application programming interface
Social search and artificial intelligence
Research future
Part IV: Agent-based web, security issues, and human–computer interaction
Agent-based web
Introduction
Agents
Typology of agents
Multiagent systems
Agent-based web
Hybridization of mobile agent and interface agent: A case for personalized content representation
Case study
Conclusion
Web security
Introduction
Web vulnerabilities
Web server protection
Security and privacy
Contributions of AI for security issues
Human–web interactions
Introduction
Features of a good website
What is interaction?
Interaction design and related parameters
Usability
Process of interaction design
Conceptual models of interaction
Interface
Interface design methods
Tools for human–web interaction
Interaction evaluation methods
Human–computer interaction and human–web interaction
Issues in human–web interactions
Support of AI for human–web interactions
Case studies
Research applications
Conclusion