Link Mining Models Algorithms (14 results)

Hardcover. Condition: Fine. This book is in excellent condition with a few colorless scuffs to the textblock and a hint of rubbing, niether are very significant. Overall, a handsome copy, nearly new.

Condition: Sehr gut. Zustand: Sehr gut | Seiten: 586 | Sprache: Englisch | Produktart: Bücher | With the recent flourishing research activities on Web search and mining, social network analysis, information network analysis, information retrieval, link analysis, and structural data mining, research on link mining has been rapidly growing, forming a new field of data mining. Traditional data mining focuses on "flat" or "isolated" data in which each data object is represented as an independent attribute vector. However, many real-world data sets are inter-connected, much richer in structure, involving objects of heterogeneous types and complex links. Hence, the study of link mining will have a high impact in various important applications such as Web and text mining, social network analysis, collaborative filtering, and bioinformatics.Link Mining: Models, Algorithms and Applications focuses on the theory and techniques as well as the related applications for link mining, especially from an interdisciplinary point of view. Due to the high popularity of linkage data, extensive applications ranging from governmental organizations to commercial businesses to people's daily life call for exploring the techniques of mining linkage data. This book provides a comprehensive coverage of the link mining models, techniques and applications. Each chapter is contributed from some well known researchers in the field.Link Mining: Models, Algorithms and Applications is designed for researchers, teachers, and advanced-level students in computer science. This book is also suitable for practitioners in industry.

Condition: New. In.

Condition: New. In.

Taschenbuch. Condition: Neu. Link Mining: Models, Algorithms, and Applications | Philip S. Yu (u. a.) | Taschenbuch | xiii | Englisch | 2014 | Springer US | EAN 9781493901470 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - With the recent flourishing research activities on Web search and mining, social network analysis, information network analysis, information retrieval, link analysis, and structural data mining, research on link mining has been rapidly growing, forming a new field of data mining. Traditional data mining focuses on 'flat' or 'isolated' data in which each data object is represented as an independent attribute vector. However, many real-world data sets are inter-connected, much richer in structure, involving objects of heterogeneous types and complex links. Hence, the study of link mining will have a high impact in various important applications such as Web and text mining, social network analysis, collaborative filtering, and bioinformatics.Link Mining: Models, Algorithms and Applications focuses on the theory and techniques as well as the related applications for link mining, especially from an interdisciplinary point of view. Due to the high popularity of linkage data, extensive applications ranging from governmental organizations to commercial businesses to people's daily life call for exploring the techniques of mining linkage data. This book provides a comprehensive coverage of the link mining models, techniques and applications. Each chapter is contributed from some well known researchers in the field.Link Mining: Models, Algorithms and Applications is designed for researchers, teachers, and advanced-level students in computer science. This book is also suitable for practitioners in industry.

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - With the recent flourishing research activities on Web search and mining, social network analysis, information network analysis, information retrieval, link analysis, and structural data mining, research on link mining has been rapidly growing, forming a new field of data mining. Traditional data mining focuses on 'flat' or 'isolated' data in which each data object is represented as an independent attribute vector. However, many real-world data sets are inter-connected, much richer in structure, involving objects of heterogeneous types and complex links. Hence, the study of link mining will have a high impact in various important applications such as Web and text mining, social network analysis, collaborative filtering, and bioinformatics.Link Mining: Models, Algorithms and Applications focuses on the theory and techniques as well as the related applications for link mining, especially from an interdisciplinary point of view. Due to the high popularity of linkage data, extensive applications ranging from governmental organizations to commercial businesses to people's daily life call for exploring the techniques of mining linkage data. This book provides a comprehensive coverage of the link mining models, techniques and applications. Each chapter is contributed from some well known researchers in the field.Link Mining: Models, Algorithms and Applications is designed for researchers, teachers, and advanced-level students in computer science. This book is also suitable for practitioners in industry.

Condition: new. Questo è un articolo print on demand.

Condition: new. Questo è un articolo print on demand.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Link mining has become an emerging field of data mining, which has a high impact in various important applications such as text mining, social network analysis, collaborative filtering, and bioinformatics This will be the first book on the market focusing o.

Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Link mining has become an emerging field of data mining, which has a high impact in various important applications such as text mining, social network analysis, collaborative filtering, and bioinformatics This will be the first book on the market focusing o.

Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -With the recent flourishing research activities on Web search and mining, social network analysis, information network analysis, information retrieval, link analysis, and structural data mining, research on link mining has been rapidly growing, forming a new field of data mining. Traditional data mining focuses on 'flat' or 'isolated' data in which each data object is represented as an independent attribute vector. However, many real-world data sets are inter-connected, much richer in structure, involving objects of heterogeneous types and complex links. Hence, the study of link mining will have a high impact in various important applications such as Web and text mining, social network analysis, collaborative filtering, and bioinformatics.Link Mining: Models, Algorithms and Applications focuses on the theory and techniques as well as the related applications for link mining, especially from an interdisciplinary point of view. Due to the high popularity of linkage data, extensive applications ranging from governmental organizations to commercial businesses to people's daily life call for exploring the techniques of mining linkage data. This book provides a comprehensive coverage of the link mining models, techniques and applications. Each chapter is contributed from some well known researchers in the field.Link Mining: Models, Algorithms and Applications is designed for researchers, teachers, and advanced-level students in computer science. This book is also suitable for practitioners in industry. 586 pp. Englisch.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -With the recent flourishing research activities on Web search and mining, social network analysis, information network analysis, information retrieval, link analysis, and structural data mining, research on link mining has been rapidly growing, forming a new field of data mining. Traditional data mining focuses on 'flat' or 'isolated' data in which each data object is represented as an independent attribute vector. However, many real-world data sets are inter-connected, much richer in structure, involving objects of heterogeneous types and complex links. Hence, the study of link mining will have a high impact in various important applications such as Web and text mining, social network analysis, collaborative filtering, and bioinformatics.Link Mining: Models, Algorithms and Applications focuses on the theory and techniques as well as the related applications for link mining, especially from an interdisciplinary point of view. Due to the high popularity of linkage data, extensive applications ranging from governmental organizations to commercial businesses to people's daily life call for exploring the techniques of mining linkage data. This book provides a comprehensive coverage of the link mining models, techniques and applications. Each chapter is contributed from some well known researchers in the field.Link Mining: Models, Algorithms and Applications is designed for researchers, teachers, and advanced-level students in computer science. This book is also suitable for practitioners in industry. 600 pp. Englisch.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Wewouldliketoconveyourappreciationtoallauthorsfortheirvaluablec- tributions. WewouldalsoliketoacknowledgethatthisworkissupportedbyNSF throughgrantsIIS-0905215,IIS-0914934,andDBI-0960443. Chicago,Illinois PhilipS. Yu Urbana-Champaign,Illinois JiaweiHan Pittsburgh,Pennsylvania ChristosFaloutsos v Contents Part I Link-Based Clustering 1 Machine Learning Approaches to Link-Based Clustering. . . . . . . . . . . 3 Zhongfei(Mark)Zhang,BoLong,ZhenGuo,TianbingXu, andPhilipS. Yu 2 Scalable Link-Based Similarity Computation and Clustering. . . . . . . . 45 XiaoxinYin,JiaweiHan,andPhilipS. Yu 3 Community Evolution and Change Point Detection in Time-Evolving Graphs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 JimengSun,SpirosPapadimitriou,PhilipS. Yu,andChristosFaloutsos Part II Graph Mining and Community Analysis 4 A Survey of Link Mining Tasks for Analyzing Noisy and Incomplete Networks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 GalileoMarkNamata,HossamSharara,andLiseGetoor 5 Markov Logic: A Language and Algorithms for Link Mining. . . . . . . 135 PedroDomingos,DanielLowd,StanleyKok,AniruddhNath,Hoifung Poon,MatthewRichardson,andParagSingla 6 Understanding Group Structures and Properties in Social Media. . . . 163 LeiTangandHuanLiu 7 Time Sensitive Ranking with Application to Publication Search. . . . . 187 XinLi,BingLiu,andPhilipS. Yu 8 Proximity Tracking on Dynamic Bipartite Graphs: Problem De nitions and Fast Solutions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 Hanghang Tong, Spiros Papadimitriou, Philip S. Yu, andChristosFaloutsos vii viii Contents 9 Discriminative Frequent Pattern-Based Graph Classi cation. . . . . . . . 237 HongCheng,XifengYan,andJiaweiHan Part III Link Analysis for Data Cleaning and Information Integration 10 Information Integration for Graph Databases. . . . . . . . . . . . . . . . . . . . . 265 Ee-PengLim,AixinSunSpringer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 600 pp. Englisch.