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Graph Mining
What does the Web look like? How can we find patterns, communities, outliers, in a social network? Which are the most central nodes in a network? These are the questions that motivate this work. Networks and graphs appear in many diverse settings, for example in social networks, computer-communication networks (intrusion detection, traffic management), protein-protein interaction networks in biology, document-text bipartite graphs in text retrieval, person-account graphs in financial fraud detection, and others. In this work, first we list several surprising patterns that real graphs tend to follow. Then we give a detailed list of generators that try to mirror these patterns. Generators are ...
Machine Learning and Knowledge Discovery in Databases
The three volume proceedings LNAI 11051 – 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. The total of 131 regular papers presented in part I and part II was carefully reviewed and selected from 535 submissions; there are 52 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier detection; applications; classification; clustering and unsupervised learning; deep learningensemble methods; and evaluation. Part II: graphs; kernel methods; learning paradigms; matrix and tensor analysis; online and active learning; pattern and sequence mining; probabilistic models and statistical methods; recommender systems; and transfer learning. Part III: ADS data science applications; ADS e-commerce; ADS engineering and design; ADS financial and security; ADS health; ADS sensing and positioning; nectar track; and demo track.
Machine Learning and Knowledge Discovery in Databases
The three volume proceedings LNAI 11051 – 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. The total of 131 regular papers presented in part I and part II was carefully reviewed and selected from 535 submissions; there are 52 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier detection; applications; classification; clustering and unsupervised learning; deep learning; ensemble methods; and evaluation. Part II: graphs; kernel methods; learning paradigms; matrix and tensor analysis; online and active learning; pattern and sequence mining; probabilistic models and statistical methods; recommender systems; and transfer learning. Part III: ADS data science applications; ADS e-commerce; ADS engineering and design; ADS financial and security; ADS health; ADS sensing and positioning; nectar track; and demo track.
Advances in Data Science
This book constitutes the thoroughly refereed post-conference proceedings of the Third International Conference on Advances in Data Science, ICIIT 2018, held in Chennai, India, in December 2018. The 11 full papers along with 4 short papers presented were carefully reviewed and selected from 74 submissions.The papers are organized in topical sections on data science foundations, data management and processing technologies, data analytics and its applications.
Graph-Powered Machine Learning
At its core, machine learning is about efficiently identifying patterns and relationships in data. Many tasks, such as finding associations among terms so you can make accurate search recommendations or locating individuals within a social network who have similar interests, are naturally expressed as graphs. Graph-Powered Machine Learning introduces you to graph technology concepts, highlighting the role of graphs in machine learning and big data platforms. You'll get an in-depth look at techniques including data source modeling, algorithm design, link analysis, classification, and clustering. As you master the core concepts, you'll explore three end-to-end projects that illustrate architec...
Computational Approaches to the Network Science of Teams
Surveys recent models and algorithms characterizing, predicting, optimizing, and explaining team performance in a variety of settings.
Proceedings of the International Conference on Interdisciplinary Research in Electronics and Instrumentation Engineering 2015
Proceedings of the International Conference on Interdisciplinary Research in Electronics and Instrumentation Engineering 2015 (ICIREIE)
Brain and Health Informatics
This book constitutes the refereed proceedings of the International Conference on Brain and Health Informatics, BHI 2013, held in Maebashi, Japan, in October 2013. The 33 revised full papers presented together with 8 workshop papers and 12 special session papers were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on thinking and perception-centric Investigations of human Information processing system; information technologies for curating, mining, managing and using big brain/health data; information technologies for healthcare; data analytics, data mining, and machine learning; and applications. The topics of the workshop papers are: mental health with ICT; and granular knowledge discovery in biomedical and active-media environments; and the topics of the special sessions are: human centered computing; neuro-robotics; and intelligent healthcare data analytics.
Information Management and Big Data
This book constitutes the refereed proceedings of the 9th Annual International Conference on Information Management and Big Data, SIMBig 2022, held in Lima, Peru, during November 16–18, 2022. The 18 full papers and 1 short paper included in this book were carefully reviewed and selected from 50 submissions. The volume presented novel methods for the analysis and management of large data, in fields like Artificial Intelligence (AI), Data Science, Machine Learning, Natural Language Processing, Semantic Web, Data-driven Software Engineering, Health Informatics.
