Introduction to Search Engines and Web Navigation.
Title:
Introduction to Search Engines and Web Navigation.
Author:
Levene, Mark.
ISBN:
9780470872703
Personal Author:
Edition:
2nd ed.
Physical Description:
1 online resource (500 pages)
Contents:
AN INTRODUCTION TO SEARCH ENGINES AND WEB NAVIGATION -- CONTENTS -- PREFACE -- LIST OF FIGURES -- CHAPTER 1 INTRODUCTION -- 1.1 Brief Summary of Chapters -- 1.2 Brief History of Hypertext and the Web -- 1.3 Brief History of Search Engines -- CHAPTER 2 THE WEB AND THE PROBLEM OF SEARCH -- 2.1 Some Statistics -- 2.1.1 Web Size Statistics -- 2.1.2 Web Usage Statistics -- 2.2 Tabular Data Versus Web Data -- 2.3 Structure of the Web -- 2.3.1 Bow-Tie Structure of the Web -- 2.3.2 Small-World Structure of the Web -- 2.4 Information Seeking on the Web -- 2.4.1 Direct Navigation -- 2.4.2 Navigation within a Directory -- 2.4.3 Navigation using a Search Engine -- 2.4.4 Problems with Web Information Seeking -- 2.5 Informational, Navigational, and Transactional Queries -- 2.6 Comparing Web Search to Traditional Information Retrieval -- 2.6.1 Recall and Precision -- 2.7 Local Site Search Versus Global Web Search -- 2.8 Difference Between Search and Navigation -- CHAPTER 3 THE PROBLEM OF WEB NAVIGATION -- 3.1 Getting Lost in Hyperspace and the Navigation Problem -- 3.2 How Can the Machine Assist in User Search and Navigation -- 3.2.1 The Potential Use of Machine Learning Algorithms -- 3.2.2 The Naive Bayes Classifier for Categorizing Web Pages -- 3.3 Trails Should be First Class Objects -- 3.4 Enter Markov Chains and Two Interpretations of Its Probabilities -- 3.4.1 Markov Chains and the Markov Property -- 3.4.2 Markov Chains and the Probabilities of Following Links -- 3.4.3 Markov Chains and the Relevance of Links -- 3.5 Conflict Between Web Site Owner and Visitor -- 3.6 Conflict Between Semantics of Web Site and the Business Model -- CHAPTER 4 SEARCHING THE WEB -- 4.1 Mechanics of a Typical Search -- 4.2 Search Engines as Information Gatekeepers of the Web -- 4.3 Search Engine Wars, is the Dust Settling? -- 4.3.1 Competitor Number One: Google.
4.3.2 Competitor Number Two: Yahoo -- 4.3.3 Competitor Number Three: Bing -- 4.3.4 Other Competitors -- 4.4 Statistics from Studies of Search Engine Query Logs -- 4.4.1 Search Engine Query Logs -- 4.4.2 Search Engine Query Syntax -- 4.4.3 The Most Popular Search Keywords -- 4.5 Architecture of a Search Engine -- 4.5.1 The Search Index -- 4.5.2 The Query Engine -- 4.5.3 The Search Interface -- 4.6 Crawling the Web -- 4.6.1 Crawling Algorithms -- 4.6.2 Refreshing Web Pages -- 4.6.3 The Robots Exclusion Protocol -- 4.6.4 Spider Traps -- 4.7 What Does it Take to Deliver a Global Search Service? -- CHAPTER 5 HOW DOES A SEARCH ENGINE WORK -- 5.1 Content Relevance -- 5.1.1 Processing Web Pages -- 5.1.2 Interpreting the Query -- 5.1.3 Term Frequency -- 5.1.4 Inverse Document Frequency -- 5.1.5 Computing Keyword TF-IDF Values -- 5.1.6 Caching Queries -- 5.1.7 Phrase Matching -- 5.1.8 Synonyms -- 5.1.9 Link Text -- 5.1.10 URL Analysis -- 5.1.11 Date Last Updated -- 5.1.12 HTML Structure Weighting -- 5.1.13 Spell Checking -- 5.1.14 Non-English Queries -- 5.1.15 Home Page Detection -- 5.1.16 Related Searches and Query Suggestions -- 5.2 Link-Based Metrics -- 5.2.1 Referential and Informational Links -- 5.2.2 Combining Link Analysis with Content Relevance -- 5.2.3 Are Links the Currency of the Web? -- 5.2.4 PageRank Explained -- 5.2.5 Online Computation of PageRank -- 5.2.6 Monte Carlo Methods in PageRank Computation -- 5.2.7 Hyperlink-Induced Topic Search -- 5.2.8 Stochastic Approach for Link-Structure Analysis -- 5.2.9 Counting Incoming Links -- 5.2.10 The Bias of PageRank against New Pages -- 5.2.11 PageRank within a Community -- 5.2.12 Influence of Weblogs on PageRank -- 5.2.13 Link Spam -- 5.2.14 Citation Analysis -- 5.2.15 The Wide Ranging Interest in PageRank -- 5.3 Popularity-Based Metrics -- 5.3.1 Direct Hit's Popularity Metric.
5.3.2 Document Space Modification -- 5.3.3 Using Query Log Data to Improve Search -- 5.3.4 Learning to Rank -- 5.3.5 BrowseRank -- 5.4 Evaluating Search Engines -- 5.4.1 Search Engine Awards -- 5.4.2 Evaluation Metrics -- 5.4.3 Performance Measures -- 5.4.4 Eye Tracking Studies -- 5.4.5 Test Collections -- 5.4.6 Inferring Ranking Algorithms -- CHAPTER 6 DIFFERENT TYPES OF SEARCH ENGINES -- 6.1 Directories and Categorization of Web Content -- 6.2 Search Engine Advertising -- 6.2.1 Paid Inclusion -- 6.2.2 Banner Ads -- 6.2.3 Sponsored Search and Paid Placement -- 6.2.4 Behavioral Targeting -- 6.2.5 User Behavior -- 6.2.6 The Trade-Off between Bias and Demand -- 6.2.7 Sponsored Search Auctions -- 6.2.8 Pay per Action -- 6.2.9 Click Fraud and Other Forms of Advertising Fraud -- 6.3 Metasearch -- 6.3.1 Fusion Algorithms -- 6.3.2 Operational Metasearch Engines -- 6.3.3 Clustering Search Results -- 6.3.4 Classifying Search Results -- 6.4 Personalization -- 6.4.1 Personalization versus Customization -- 6.4.2 Personalized Results Tool -- 6.4.3 Privacy and Scalability -- 6.4.4 Relevance Feedback -- 6.4.5 Personalized PageRank -- 6.4.6 Outride's Personalized Search -- 6.5 Question Answering (Q&A) on the Web -- 6.5.1 Natural Language Annotations -- 6.5.2 Factual Queries -- 6.5.3 Open Domain Question Answering -- 6.5.4 Semantic Headers -- 6.6 Image Search -- 6.6.1 Text-Based Image Search -- 6.6.2 Content-Based Image Search -- 6.6.3 VisualRank -- 6.6.4 CAPTCHA and reCAPTCHA -- 6.6.5 Image Search for Finding Location-Based Information -- 6.7 Special Purpose Search Engines -- CHAPTER 7 NAVIGATING THE WEB -- 7.1 Frustration in Web Browsing and Navigation -- 7.1.1 HTML and Web Site Design -- 7.1.2 Hyperlinks and Surfing -- 7.1.3 Web Site Design and Usability -- 7.2 Navigation Tools -- 7.2.1 The Basic Browser Tools -- 7.2.2 The Back and Forward Buttons.
7.2.3 Search Engine Toolbars -- 7.2.4 The Bookmarks Tool -- 7.2.5 The History List -- 7.2.6 Identifying Web Pages -- 7.2.7 Breadcrumb Navigation -- 7.2.8 Quicklinks -- 7.2.9 Hypertext Orientation Tools -- 7.2.10 Hypercard Programming Environment -- 7.3 Navigational Metrics -- 7.3.1 The Potential Gain -- 7.3.2 Structural Analysis of a Web Site -- 7.3.3 Measuring the Usability of Web Sites -- 7.4 Web Data Mining -- 7.4.1 Three Perspectives on Data Mining -- 7.4.2 Measuring the Success of a Web Site -- 7.4.3 Web Analytics -- 7.4.4 E-Metrics -- 7.4.5 Web Analytics Tools -- 7.4.6 Weblog File Analyzers -- 7.4.7 Identifying the Surfer -- 7.4.8 Sessionizing -- 7.4.9 Supplementary Analyses -- 7.4.10 Markov Chain Model of Web Site Navigation -- 7.4.11 Applications of Web Usage Mining -- 7.4.12 Information Extraction -- 7.5 The Best Trail Algorithm -- 7.5.1 Effective View Navigation -- 7.5.2 Web Usage Mining for Personalization -- 7.5.3 Developing a Trail Engine -- 7.6 Visualization that Aids Navigation -- 7.6.1 How to Visualize Navigation Patterns -- 7.6.2 Overview Diagrams and Web Site Maps -- 7.6.3 Fisheye Views -- 7.6.4 Visualizing Trails within a Web Site -- 7.6.5 Visual Search Engines -- 7.6.6 Social Data Analysis -- 7.6.7 Mapping Cyberspace -- 7.7 Navigation in Virtual and Physical Spaces -- 7.7.1 Real-World Web Usage Mining -- 7.7.2 The Museum Experience Recorder -- 7.7.3 Navigating in the Real World -- CHAPTER 8 THE MOBILE WEB -- 8.1 The Paradigm of Mobile Computing -- 8.1.1 Wireless Markup Language -- 8.1.2 The i-mode Service -- 8.2 Mobile Web Services -- 8.2.1 M-commerce -- 8.2.2 Delivery of Personalized News -- 8.2.3 Delivery of Learning Resources -- 8.3 Mobile Device Interfaces -- 8.3.1 Mobile Web Browsers -- 8.3.2 Information Seeking on Mobile Devices -- 8.3.3 Text Entry on Mobile Devices -- 8.3.4 Voice Recognition for Mobile Devices.
8.3.5 Presenting Information on a Mobile Device -- 8.4 The Navigation Problem in Mobile Portals -- 8.4.1 Click-Distance -- 8.4.2 Adaptive Mobile Portals -- 8.4.3 Adaptive Web Navigation -- 8.5 Mobile Search -- 8.5.1 Mobile Search Interfaces -- 8.5.2 Search Engine Support for Mobile Devices -- 8.5.3 Focused Mobile Search -- 8.5.4 Laid Back Mobile Search -- 8.5.5 Mobile Query Log Analysis -- 8.5.6 Personalization of Mobile Search -- 8.5.7 Location-Aware Mobile Search -- CHAPTER 9 SOCIAL NETWORKS -- 9.1 What is a Social Network? -- 9.1.1 Milgram's Small-World Experiment -- 9.1.2 Collaboration Graphs -- 9.1.3 Instant Messaging Social Network -- 9.1.4 The Social Web -- 9.1.5 Social Network Start-Ups -- 9.2 Social Network Analysis -- 9.2.1 Social Network Terminology -- 9.2.2 The Strength of Weak Ties -- 9.2.3 Centrality -- 9.2.4 Web Communities -- 9.2.5 Pajek: Large Network Analysis Software -- 9.3 Peer-to-Peer Networks -- 9.3.1 Centralized P2P Networks -- 9.3.2 Decentralized P2P Networks -- 9.3.3 Hybrid P2P Networks -- 9.3.4 Distributed Hash Tables -- 9.3.5 BitTorrent File Distribution -- 9.3.6 JXTA P2P Search -- 9.3.7 Incentives in P2P Systems -- 9.4 Collaborative Filtering -- 9.4.1 Amazon.com -- 9.4.2 Collaborative Filtering Explained -- 9.4.3 User-Based Collaborative Filtering -- 9.4.4 Item-Based Collaborative Filtering -- 9.4.5 Model-Based Collaborative Filtering -- 9.4.6 Content-Based Recommendation Systems -- 9.4.7 Evaluation of Collaborative Filtering Systems -- 9.4.8 Scalability of Collaborative Filtering Systems -- 9.4.9 A Case Study of Amazon.co.uk -- 9.4.10 The Netflix Prize -- 9.4.11 Some Other Collaborative Filtering Systems -- 9.5 Weblogs (Blogs) -- 9.5.1 Blogrolling -- 9.5.2 Blogspace -- 9.5.3 Blogs for Testing Machine Learning Algorithms -- 9.5.4 Spreading Ideas via Blogs -- 9.5.5 The Real-Time Web and Microblogging.
9.6 Power-Law Distributions in the Web.
Abstract:
An authoritative, easy-to-follow primer on the underlying computational tools of Web search and navigation Search and navigation technologies are central to the smooth operation of the Web, and have changed the way we seek out and interact with information. Understanding the computational basis of these technologies and the models underlying them is of paramount importance to both computing students and practitioners. This Second Edition contains up-to-date, unrivalled coverage, bridging the gap between technically based and sociologically oriented Web books. It demystifies the tools that we use when interacting with the Web, as well as models different aspects of the Web that can help us understand how it is evolving-and how it is being, and can be, effectively used. The first part of the book covers the historical background of hypertext, the Web, and search engines and introduces the problems of search and navigation, discussing the potential of machine learning to improve search and navigation tools and proposing Markov chains as a model for user navigation. The second part explains the architectural and technical aspects of search engines. Described here are the search engine wars, the architecture of a search engine and details of how the Web is crawled, a search engine's ranking algorithm, and different ways of evaluating search engines. Then, different types of search engines are explored, including Web directories, search engine advertising, metasearch engines, personalization of search, question-answering engines, image search, and special purpose engines. The final part concentrates on Web navigation, the mobile Web, and social network technologies in the context of search and navigation. Discussed are a range of navigation tools and metrics; Web data mining and visualization of Web navigation; the issues present in real-world
navigation; the delivery of mobile Web services and the problems of search and navigation in a mobile context; peer-to-peer networks; the technology of collaborative filtering; Weblogs as a medium for personal journalism; social tagging and bookmarking; opinion mining; Web 2.0; and collective intelligence. Each chapter begins with objectives and concludes with a summary and several exercises. Many real-world technology examples are provided throughout, including social networking, data mining, and nontraditional search engines. This book is intended as an undergraduate introductory text on search and navigation technologies. It is also ideal for IT professionals who wish to understand how these technologies work and what the future holds.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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