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Web-Age Information Management
Database research and development has been remarkably successful over the past three decades. Now the field is facing new challenges posted by the rapid advances of technology, especially the penetration of the Web and Internet into everyone's daily life. The economical and financial environment where database systems are used has been changing dramatically. In addition to being able to efficiently manage a large volume of operational data generated internally, the ability to manage data in cyberspace, extract relevant information, and discover knowledge to support decision making is critical to the success of any organization. In order to provide researchers and practitioners with a forum t...
On the Move to Meaningful Internet Systems 2002: CoopIS, DOA, and ODBASE
This book constitutes the refereed proceedings of the three confederated conferences CoopIS 2002, DOA 2002, and ODBASE 2002, held in Irvine, CA, USA, in October/November 2002. The 77 revised full papers and 10 posters presented were carefully reviewed and selected from a total of 291 submissions. The papers are organized in topical sections on interoperability, workflow, mobility, agents, peer-to-peer and ubiquitous, work process, business and transaction, infrastructure, query processing, quality issues, agents and middleware, cooperative systems, ORB enhancements, Web services, distributed object scalability and heterogeneity, dependability and security, reflection and reconfiguration, real-time scheduling, component-based applications, ontology languages, conceptual modeling, ontology management, ontology development and engineering, XML and data integration, and tools for the intelligent Web.
Conceptual Modeling - ER 2001
This book constitutes the refereed proceedings of the 20th International Conference on Conceptual Modeling, ER 2001, held in Tokohama, Japan, in November 2001. The 45 revised full papers presented together with three keynote presentations were carefully reviewed and selected from a total of 197 submissions. The papers are organized in topical sections on spatial databases, spatio-temporal databases, XML, information modeling, database design, data integration, data warehouse, UML, conceptual models, systems design, method reengineering and video databases, workflows, web information systems, applications, and software engineering.
Sentiment Analysis
A comprehensive introduction to computational analysis of sentiments, opinions, emotions, and moods. Now including deep learning methods.
Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing 2012
The purpose of the 13th International Conference on Computer and Information Science (SNPD 2012) held on August 8-10, 2012 in Kyoto, Japan was to bring together researchers and scientists, businessmen and entrepreneurs, teachers and students to discuss the numerous fields of computer science, and to share ideas and information in a meaningful way. Our conference officers selected the best 17 papers from those papers accepted for presentation at the conference in order to publish them in this volume. The papers were chosen based on review scores submitted by members of the program committee, and underwent further rounds of rigorous review. The conference organizers selected 17 outstanding papers from SNPD 2012, all of which you will find in this volume of Springer’s Studies in Computational Intelligence.
Technologies for E-Services
This book constitutes the refereed preceedings of the Third International Workshop on Technologies for E-Servies, TES 2002, held in conjunction with VLDB 2002 in Hong Kong, China in August 2002. The 14 revised full papers presented together with 4 invited papers were carefully reviewed and selected. Among the topics addressed are database issues for e-services, b2b integration, model transformation, process-based application development, information fusion, information integration, business relation management, mobil servies, trust-based web security models, etc.
Lifelong Machine Learning, Second Edition
Lifelong Machine Learning, Second Edition is an introduction to an advanced machine learning paradigm that continuously learns by accumulating past knowledge that it then uses in future learning and problem solving. In contrast, the current dominant machine learning paradigm learns in isolation: given a training dataset, it runs a machine learning algorithm on the dataset to produce a model that is then used in its intended application. It makes no attempt to retain the learned knowledge and use it in subsequent learning. Unlike this isolated system, humans learn effectively with only a few examples precisely because our learning is very knowledge-driven: the knowledge learned in the past he...
Lifelong Machine Learning
Lifelong Machine Learning (or Lifelong Learning) is an advanced machine learning paradigm that learns continuously, accumulates the knowledge learned in previous tasks, and uses it to help future learning. In the process, the learner becomes more and more knowledgeable and effective at learning. This learning ability is one of the hallmarks of human intelligence. However, the current dominant machine learning paradigm learns in isolation: given a training dataset, it runs a machine learning algorithm on the dataset to produce a model. It makes no attempt to retain the learned knowledge and use it in future learning. Although this isolated learning paradigm has been very successful, it requir...
Data Warehousing and Knowledge Discovery
This book constitutes the refereed proceedings of the First International Conference on Data Warehousing and Knowledge Discovery, DaWaK'99, held in Florence, Italy in August/September 1999. The 31 revised full papers and nine short papers presented were carefully reviewed and selected from 88 submissions. The book is divided in topical sections on data warehouse design; online analytical processing; view synthesis, selection, and optimization; multidimensional databases; knowledge discovery; association rules; inexing and object similarities; generalized association rules and data and web mining; time series data bases; data mining applications and data analysis.
Advances in Visual Information Management
Video segmentation is the most fundamental process for appropriate index ing and retrieval of video intervals. In general, video streams are composed 1 of shots delimited by physical shot boundaries. Substantial work has been done on how to detect such shot boundaries automatically (Arman et aI. , 1993) (Zhang et aI. , 1993) (Zhang et aI. , 1995) (Kobla et aI. , 1997). Through the inte gration of technologies such as image processing, speech/character recognition and natural language understanding, keywords can be extracted and associated with these shots for indexing (Wactlar et aI. , 1996). A single shot, however, rarely carries enough amount of information to be meaningful by itself. Usu ...
