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Intelligent Exploration of the Web 1st Edition by Kyong Ho Lee ISBN 3790825190 9783790825190

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Author(s): Kyong Ho Lee, Yoon Chul Choy, Sung-Bae Cho (auth.), Associate Professor Dr. Piotr S. Szczepaniak, Associate Professor Dr. Javier Segovia, Professor Dr. Janusz Kacprzyk, Professor Dr. Lotfi A. Zadeh (eds.)
ISBN(s): 9783790825190, 3790825190
Edition: 1
File Details: PDF, 21.12 MB
Year: 2003
Language: english
SKU: EB-4200750 Category: Tags: , , , , , ,

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ISBN 10: 3790825190 
ISBN 13: 9783790825190
Author: Kyong Ho Lee

The Web is the nervous system of information society. As such, it has a pervasive influence on our daily lives. And yet, in some ways the Web does not have a high MIQ (Machine IQ). What can be done to enhance it? This is the leitmotif of “Intelligent Exploration of the Web,” (lEW)–a collection of articles co-edited by Drs. Szczepaniak, Segovia, Kacprzyk and, to a small degree, myself. The articles that comprise lEW address many basic problems ranging from structure analysis of Internet documents and Web dialogue management to intelligent Web agents for extraction of information, and bootstrapping an ontology-based information extraction system. Among the basic problems, one that stands out in importance is the problem of search. Existing search engines have many remarkable capabilities. But what is not among them is the deduction capability–the capability to answer a query by drawing on information which resides in various parts of the knowledge base. An example of a query might be “How many Ph.D. degrees in computer science were granted by European universities in 1996?” No existing search engine is capable of dealing with queries of comparable or even much lower complexity. Basically, what we would like to do is to add deduction capability to a search engine, with the aim of transforming it into a question-answering system, or a QI A system, for short. This is a problem that is of major importance and a challenge that is hard to meet.

Intelligent Exploration of the Web 1st Table of contents:

Chapter 1: Introduction

  • The Web as an Information Space

  • Challenges in Web Exploration

  • Overview of Intelligent Exploration

Chapter 2: Web Structure and Data Models

  • The Web Graph

  • Data Models for the Web

  • Semantic Web Concepts

Chapter 3: Crawling and Indexing

  • Web Crawling Techniques

  • Focused Crawling

  • Indexing Strategies

Chapter 4: Information Retrieval and Ranking

  • Retrieval Models

  • Ranking Algorithms

  • Personalized Search

Chapter 5: Machine Learning for Web Exploration

  • Supervised and Unsupervised Learning

  • Reinforcement Learning

  • Application to Web Tasks

Chapter 6: User Interaction and Behavior Analysis

  • User Modeling

  • Clickstream Analysis

  • Adaptive Interfaces

Chapter 7: Semantic Web and Ontologies

  • Ontology Design

  • Semantic Annotation

  • Reasoning on the Web

Chapter 8: Applications of Intelligent Web Exploration

  • Recommendation Systems

  • Web Mining

  • Social Network Analysis

Chapter 9: Future Directions and Challenges

  • Scalability and Big Data

  • Privacy and Ethics

  • Emerging Technologies

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Tags: Kyong Ho Lee, Intelligent Exploration, Web