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Learning Structure and Schemas from Documents
The rapidly growing volume of available digital documents of various formats and the possibility to access these through Internet-based technologies, have led to the necessity to develop solid methods to properly organize and structure documents in large digital libraries and repositories. Due to the extremely large volumes of documents and to their unstructured form, most of the research efforts in this direction are dedicated to automatically infer structure and schemas that can help to better organize huge collections of documents and data. This book covers the latest advances in structure inference in heterogeneous collections of documents and data. The book brings a comprehensive view o...
Machine Learning and Knowledge Discovery in Databases
The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022. The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions. The volumes are organized in topical sections as follows: Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge grap...
Engineering Mathematics and Artificial Intelligence
The fields of Artificial Intelligence (AI) and Machine Learning (ML) have grown dramatically in recent years, with an increasingly impressive spectrum of successful applications. This book represents a key reference for anybody interested in the intersection between mathematics and AI/ML and provides an overview of the current research streams. Engineering Mathematics and Artificial Intelligence: Foundations, Methods, and Applications discusses the theory behind ML and shows how mathematics can be used in AI. The book illustrates how to improve existing algorithms by using advanced mathematics and offers cutting-edge AI technologies. The book goes on to discuss how ML can support mathematical modeling and how to simulate data by using artificial neural networks. Future integration between ML and complex mathematical techniques is also highlighted within the book. This book is written for researchers, practitioners, engineers, and AI consultants.
Database and Expert Systems Applications
This book constitutes the refereed proceedings of the 22 International Conference on Database and Expert Systems Applications, DEXA 2011, held in Toulouse, France, August 29 - September 2, 2011. The 52 revised full papers and 40 short papers presented were carefully reviewed and selected from 207 submissions. The papers are organized in topical sections on query processing; database semantics; skyline queries; security and privacy; spatial and temporal data; semantic web search; storage and search; web search; data integration, transactions and optimization; and web applications.
Intelligent Systems in Industrial Applications
This book presents a selection of papers from the industrial track of ISMIS 2020. The selection emphasizes broad applicability of artificial intelligence (AI) technologies in various industrial fields. The aim of the book is to fertilize preliminary ideas of readers on the application of AI by means of already successfully implemented application examples. Furthermore, the development of new ideas and concepts shall be motivated by the variety of different application examples. The spectrum of the presented contributions ranges from education and training, industrial applications in production and logistics to the development of new approaches in basic research, which will further expand the possibilities of future applications of AI in industrial settings. This broad spectrum gives readers working in the industrial as well as the academic field a good overview of the state of the art in the field of methodologies for intelligent systems.
Machine Learning and Knowledge Discovery in Databases
The 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was held during September 14-18, 2020. The conference was planned to take place in Ghent, Belgium, but had to change to an online format due to the COVID-19 pandemic. The 232 full papers and 10 demo papers presented in this volume were carefully reviewed and selected for inclusion in the proceedings. The volumes are organized in topical sections as follows: Part I: Pattern Mining; clustering; privacy and fairness; (social) network analysis and computational social science; dimensionality reduction and ...
Digital Libraries and Archives
This book constitutes the thoroughly refereed proceedings of the 8th Italian Research Conference on Digital Libraries, held in Bari, Italy, in February 2012. The 22 full papers, included together with 4 panel papers, were selected from extended versions of the presentations given at the conference, following an additional round of reviewing and revision after the event. The topics covered are as follows: legacy documents and cultural heritage; systems interoperability and data integration; formal and methodological foundations of digital libraries; semantic web and linked data for digital libraries; multilingual information access; digital library infrastructures; metadata creation and management; search engines for digital library systems; evaluation and log data; handling audio/visual and non-traditional objects; user interfaces and visualization; digital library quality; policies and copyright issues in digital libraries; scientific data curation, citation and scholarly publication, user behavior and modeling; and preservation and curation.
Machine Learning and Knowledge Discovery in Databases
The three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. The 131 papers presented in these proceedings were carefully reviewed and selected from a total of 483 submissions. These include 89 research papers, 11 industrial papers, 14 nectar papers, and 17 demo papers. They were organized in topical sections named: classification, regression and supervised learning; clustering and unsupervised learning; data preprocessing; data streams and online learning; deep learning; distance and metric learning; large scale learning and big data; matrix and tensor analysis; pattern and sequence mining; preference learning and label ranking; probabilistic, statistical, and graphical approaches; rich data; and social and graphs. Part III is structured in industrial track, nectar track, and demo track.
