{"product_id":"graph-mining-laws-tools-and-case-studies-practical-network","title":"Graph Mining: Laws, Tools, and Case Studies - Practical Network","description":"\u003cp\u003eIn this review of Graph Mining: Laws, Tools, and Case Studies the authors present a focused, research-driven examination of how real networks behave and how to analyze them. This book is for readers who need a compact, methodical guide to recognizing empirical patterns in graphs and to using generators for simulation, extrapolation, and anonymization. The single biggest reason to read it is its clear connection between observed \u003cstrong\u003ereal-graph patterns\u003c\/strong\u003e and practical tools that reproduce those patterns for experimentation and applied analysis.\u003c\/p\u003e\u003ch2\u003eKey Features\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eEmpirical patterns:\u003c\/strong\u003e Summarizes surprising, repeatedly observed structural regularities in real networks to ground analysis in data.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eGraph generators:\u003c\/strong\u003e Provides a detailed list of generators that mirror observed patterns, useful for what-if scenarios and synthetic data creation.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eApplications overview:\u003c\/strong\u003e Connects graph analysis to diverse domains such as social networks, intrusion detection, and biology to show practical relevance.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eFocus on tools:\u003c\/strong\u003e Emphasizes usable techniques for finding communities, outliers, and central nodes rather than only theory.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAnonymization use:\u003c\/strong\u003e Explains how generators can assist in anonymizing network data while retaining key structural properties.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eWho It's For\u003c\/h2\u003e\u003cp\u003eThis book is aimed at graduate students, researchers, and practitioners in data mining, network science, and applied machine learning who want a compact reference linking observed graph phenomena to modeling tools. It works well as a supplemental course text or a practitioner's handbook for designing experiments or simulations.\u003c\/p\u003e\u003cp\u003eReaders seeking an introductory textbook on basic graph theory or a broad survey of algorithms may want a more general treatment; this volume assumes interest in real-world patterns and generator-based approaches rather than elementary proofs and algorithmic details.\u003c\/p\u003e\u003ch2\u003ePros \u0026amp; Cons\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003ePros\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eConcise presentation of \u003cstrong\u003ereal graph laws\u003c\/strong\u003e that helps prioritize what to model.\u003c\/li\u003e\n\u003cli\u003ePractical catalog of generators that make \u003cstrong\u003esynthetic graph experiments\u003c\/strong\u003e feasible.\u003c\/li\u003e\n\u003cli\u003eClear links to applications such as fraud detection and protein interaction analysis that highlight usefulness.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cstrong\u003eCons\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\u003cli\u003eNot a beginner's primer on graph theory, so readers without prior exposure may need supplementary background.\u003c\/li\u003e\u003c\/ul\u003e\u003ch2\u003eSpecifications\u003c\/h2\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003eTitle\u003c\/td\u003e\n\u003ctd\u003eGraph Mining: Laws, Tools, and Case Studies\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eSeries\u003c\/td\u003e\n\u003ctd\u003eSynthesis Lectures on Data Mining and Knowledge Discovery\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAuthors\u003c\/td\u003e\n\u003ctd\u003eDeepayan Chakrabarti, Christos Faloutsos\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFocus topics\u003c\/td\u003e\n\u003ctd\u003eGraph patterns, generators, communities, outliers, centrality\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eApplication domains\u003c\/td\u003e\n\u003ctd\u003eSocial networks, intrusion detection, biology, text retrieval, fraud\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eUse cases\u003c\/td\u003e\n\u003ctd\u003eSimulation, extrapolation, anonymization, analysis\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e\u003ch2\u003eOur Verdict\u003c\/h2\u003e\u003cp\u003eGraph Mining is a compact, applied resource that convincingly ties observed network phenomena to concrete modeling tools, making it a worthwhile read for researchers and practitioners who need realistic synthetic data and guidance on spotting communities, outliers, and central nodes. It represents good value for those focused on applied network analysis rather than introductory theory.\u003c\/p\u003e\u003ch2\u003eFrequently Asked Questions\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eDoes the book include practical tools for generating synthetic graphs?\u003c\/strong\u003e\u003cbr\u003eYes, it gives a detailed list of graph generators intended to reproduce observed patterns for simulation and anonymization.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWhat kinds of networks are discussed?\u003c\/strong\u003e\u003cbr\u003eThe text covers a range of networks including social networks, computer-communication graphs, protein interaction networks, and document-text bipartite graphs.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eIs this suitable as a first textbook on graphs?\u003c\/strong\u003e\u003cbr\u003eNot ideal as a first textbook; it assumes familiarity with basic graph concepts and focuses on empirical patterns and generators.\u003c\/p\u003e","brand":"Deepayan Chakrabarti, Christos Faloutsos","offers":[{"title":"Default Title","offer_id":48628922384603,"sku":"3031007751","price":37.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0724\/1043\/1707\/files\/41MJwT9eaXL._SL1018.jpg?v=1778448486","url":"https:\/\/gearmusthave.com\/products\/graph-mining-laws-tools-and-case-studies-practical-network","provider":"GearMustHave","version":"1.0","type":"link"}