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This book lays out the theoretical groundwork for personalized search and reputation management, both on the Web and in peer-to-peer and social networks. Representing much of the foundational research in this field, the book develops scalable algorithms that exploit the graphlike properties underlying personalized search and reputation management, and delves into realistic scenarios regarding Web-scale data. Sep Kamvar focuses on eigenvector-based techniques in Web search, introducing a personalized variant of Google's PageRank algorithm, and he outlines algorithms--such as the now-famous quadratic extrapolation technique--that speed up computation, making personalized PageRank feasible. Kamvar suggests that Power Method-related techniques ultimately should be the basis for improving the PageRank algorithm, and he presents algorithms that exploit the convergence behavior of individual components of the PageRank vector. Kamvar then extends the ideas of reputation management and personalized search to distributed networks like peer-to-peer and social networks. He highlights locality and computational considerations related to the structure of the network, and considers such unique issues as malicious peers. He describes the EigenTrust algorithm and applies various PageRank concepts to P2P settings. Discussion chapters summarizing results conclude the book's two main sections. Clear and thorough, this book provides an authoritative look at central innovations in search for all of those interested in the subject.

Database searching --- Information networks --- Content analysis (Communication) --- Self-organizing systems --- Algorithms. --- Internet searching --- Analysis of content (Communication) --- Communication --- Subject analysis --- Searching the Internet --- Web searching --- World Wide Web searching --- Electronic information resource searching --- Algorism --- Algebra --- Arithmetic --- Automated information networks --- Networks, Information --- Information services --- Information storage and retrieval systems --- Data base searching --- Database search strategies --- Search strategies in databases --- Searching databases --- Mathematics. --- Data processing. --- Content analysis --- Methodology --- Foundations

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Multi-database mining is recognized as an important and strategic area of research in data mining. The authors discuss the essential issues relating to the systematic and efficient development of multi-database mining applications, and present approaches to the development of data warehouses at different branches, demonstrating how carefully selected multi-database mining techniques contribute to successful real-world applications. In showing and quantifying how the efficiency of a multi-database mining application can be improved by processing more patterns, the book also covers other essential design aspects. These are carefully investigated and include a determination of an appropriate multi-database mining model, how to select relevant databases, choosing an appropriate pattern synthesizing technique, representing pattern space, and constructing an efficient algorithm. The authors illustrate each of these development issues either in the context of a specific problem at hand, or via some general settings. Developing Multi-Database Mining Applications will be welcomed by practitioners, researchers and students working in the area of data mining and knowledge discovery.

Data mining -- Software. --- Data warehousing. --- DataMind. --- Data mining --- Engineering & Applied Sciences --- Computer Science --- Database searching --- Data base searching --- Database search strategies --- Search strategies in databases --- Searching databases --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Computer science. --- Data mining. --- Information storage and retrieval. --- Computer Science. --- Data Mining and Knowledge Discovery. --- Information Storage and Retrieval. --- Computer Science, general. --- Information Systems Applications (incl. Internet). --- Informatics --- Science --- Electronic information resource searching --- Information storage and retrieva. --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Application software. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software

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Over the course of the last twenty years, research in data mining has seen a substantial increase in interest, attracting original contributions from various disciplines including computer science, statistics, operations research, and information systems. Data mining supports a wide range of applications, from medical decision making, bioinformatics, web-usage mining, and text and image recognition to prominent business applications in corporate planning, direct marketing, and credit scoring. Research in information systems equally reflects this inter- and multidisciplinary approach, thereby advocating a series of papers at the intersection of data mining and information systems research. This special issue of Annals of Information Systems contains original papers and substantial extensions of selected papers from the 2007 and 2008 International Conference on Data Mining (DMIN’07 and DMIN’08, Las Vegas, NV) that have been rigorously peer-reviewed. The issue brings together topics on both information systems and data mining, and aims to give the reader a current snapshot of the contemporary research and state of the art practice in data mining.

Data mining. --- Data mining --- Engineering & Applied Sciences --- Management --- Management Theory --- Computer Science --- Business & Economics --- Database searching. --- Data base searching --- Database search strategies --- Search strategies in databases --- Searching databases --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Computer science. --- Business. --- Management science. --- Operations research. --- Decision making. --- Statistics. --- Engineering economics. --- Engineering economy. --- Computer Science. --- Data Mining and Knowledge Discovery. --- Operation Research/Decision Theory. --- Business and Management, general. --- Information Systems Applications (incl. Internet). --- Engineering Economics, Organization, Logistics, Marketing. --- Statistics for Business/Economics/Mathematical Finance/Insurance. --- Database searching --- Electronic information resource searching --- Operations Research/Decision Theory. --- Statistics for Business, Management, Economics, Finance, Insurance. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Economy, Engineering --- Engineering economics --- Industrial engineering --- Trade --- Economics --- Commerce --- Industrial management --- Operational analysis --- Operational research --- Management science --- Research --- System theory --- Application software. --- Statistics . --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Quantitative business analysis --- Problem solving --- Operations research --- Statistical decision --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management decisions --- Choice (Psychology) --- Decision making