{"product_id":"managing-and-mining-graph-data-comprehensive-survey-for-researchers","title":"Managing and Mining Graph Data - Comprehensive Survey for Researchers","description":"\u003cp\u003eIn this review of Managing and Mining Graph Data, the bottom line is clear: this volume is an academic, research-focused survey ideal for graduate students, professors and practitioners who need a broad, authoritative map of graph data topics. The book's greatest strength is its comprehensive collection of chapter-length surveys written by established researchers, offering clear overviews of areas from graph languages to privacy. For readers seeking a single reference that summarizes methods, domain scenarios and challenges in graph processing, this book provides a focused, technical perspective rather than an introductory textbook.\u003c\/p\u003e\u003ch2\u003eKey Features\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComprehensive surveys:\u003c\/strong\u003e Each chapter offers an extended survey of a specific graph topic, making it easy to catch up on established research directions.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWide topic coverage:\u003c\/strong\u003e The book includes material on graph languages, indexing, clustering, data generation, pattern mining and classification, which helps readers connect related areas.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eDomain perspectives:\u003c\/strong\u003e Sections on stream mining, web graphs, social networks and chemical and biological data show how graph techniques apply across domains.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eExpert contributors:\u003c\/strong\u003e Chapters are written by well known researchers, providing authoritative summaries and curated references for further study.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eResearch utility:\u003c\/strong\u003e Designed for professors and practitioners, the volume supports literature reviews, course reading lists and project scoping in graph data processing.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eWho It's For\u003c\/h2\u003e\u003cp\u003eThis book is best suited to graduate students, researchers and industry practitioners who already have a background in databases or data mining and who need a thorough survey of graph-related research topics. It functions well as a reference to identify methods, open problems and key citations across subfields.\u003c\/p\u003e\u003cp\u003eThose looking for a gentle, hands-on introduction, tutorial exercises or implementation-focused guidance should look elsewhere; this volume emphasizes surveys and scholarly perspective rather than step-by-step tutorials or code examples.\u003c\/p\u003e\u003ch2\u003ePros \u0026amp; Cons\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003ePros\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eBroad, well-structured surveys that save time when surveying the literature.\u003c\/li\u003e\n\u003cli\u003eCoverage of both algorithms and domain-specific scenarios gives practical context.\u003c\/li\u003e\n\u003cli\u003eContributions from established researchers lend credibility and depth.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cstrong\u003eCons\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\u003cli\u003eThe book is survey-focused and does not provide implementation details or hands-on tutorials, which may limit immediate practical adoption for engineers.\u003c\/li\u003e\u003c\/ul\u003e\u003ch2\u003eSpecifications\u003c\/h2\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003eTitle\u003c\/td\u003e\n\u003ctd\u003eManaging and Mining Graph Data (Advances in Database Systems, 40)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eEditor \/ Author\u003c\/td\u003e\n\u003ctd\u003eCharu C. AggarwalCharu C. Aggarwal\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eContent type\u003c\/td\u003e\n\u003ctd\u003eComprehensive survey book covering multiple graph topics\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eTopics included\u003c\/td\u003e\n\u003ctd\u003eGraph languages, indexing, clustering, pattern mining, classification, privacy\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eDomain focus\u003c\/td\u003e\n\u003ctd\u003eStream mining, web graphs, social networks, chemical and biological data\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAudience\u003c\/td\u003e\n\u003ctd\u003eProfessors, researchers, industry practitioners\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e\u003ch2\u003eOur Verdict\u003c\/h2\u003e\u003cp\u003eManaging and Mining Graph Data is a strong, focused survey volume that belongs on the shelf of anyone researching graph data processing. It delivers high value as a literature compendium and domain sampler; buy it if you need authoritative overviews and pointers to primary research, but not if you want tutorial-style, implementation-ready content.\u003c\/p\u003e\u003ch2\u003eFrequently Asked Questions\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eIs this book suitable for beginners?\u003c\/strong\u003e\u003cbr\u003eThe book assumes some background in databases or data mining; beginners may find it dense and should supplement it with introductory texts.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eDoes it include practical code or implementations?\u003c\/strong\u003e\u003cbr\u003eNo, the volume focuses on surveys and theory rather than step-by-step code or software walkthroughs.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWho wrote the chapters?\u003c\/strong\u003e\u003cbr\u003eChapters are written by well known researchers in the field, providing authoritative summaries and reference lists.\u003c\/p\u003e","brand":"Charu C. 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