جزئیات کتاب
فرمت
جلد سخت
صفحات
586
زبان
انگلیسی
منتشر شده
Jan 1, 2007
ناشر
The MIT Press
ISBN-10
0262072882
ISBN-13
9780262072885
توضیحات
In a rapidly evolving field where statistical methods converge with relational learning, this book offers an insightful introduction to the innovative techniques that define statistical relational learning. The authors, Lise Getoor and Ben Taskar, skillfully guide readers through the complexities of integrating statistical models with relational data, making complex concepts accessible.
With clear explanations and practical examples, the text delves into the foundational principles of the subject. Readers will explore various approaches to modeling relationships and uncertainty in data, equipping them with the tools needed to tackle challenging problems in diverse domains. The blend of theoretical insights and practical applications helps bridge the gap between academia and real-world scenarios.
Moreover, the authors highlight the significant impact of statistical relational learning in areas such as social network analysis, bioinformatics, and machine learning. Their expertise provides a rich context for understanding how these techniques can generate profound insights and drive innovation in research and industry. This work is an essential resource for those looking to deepen their understanding of this dynamic field.
With clear explanations and practical examples, the text delves into the foundational principles of the subject. Readers will explore various approaches to modeling relationships and uncertainty in data, equipping them with the tools needed to tackle challenging problems in diverse domains. The blend of theoretical insights and practical applications helps bridge the gap between academia and real-world scenarios.
Moreover, the authors highlight the significant impact of statistical relational learning in areas such as social network analysis, bioinformatics, and machine learning. Their expertise provides a rich context for understanding how these techniques can generate profound insights and drive innovation in research and industry. This work is an essential resource for those looking to deepen their understanding of this dynamic field.