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The proliferation of digital computing devices and their use in communication has resulted in an increased demand for systems and algorithms capable of mining textual data. Thus, the development of techniques for mining unstructured, semi-structured, and fully-structured textual data has become increasingly important in both academia and industry. This second volume continues to survey the evolving field of text mining - the application of techniques of machine learning, in conjunction with natural language processing, information extraction and algebraic/mathematical approaches, to computational information retrieval. Numerous diverse issues are addressed, ranging from the development of new learning approaches to novel document clustering algorithms, collectively spanning several major topic areas in text mining. Features: a [ Acts as an important benchmark in the development of current and future approaches to mining textual information a [ Serves as an excellent companion text for courses in text and data mining, information retrieval and computational statistics a [ Experts from academia and industry share their experiences in solving large-scale retrieval and classification problems a [ Presents an overview of current methods and software for text mining a [ Highlights open research questions in document categorization and clustering, and trend detection a [ Describes new application problems in areas such as email surveillance and anomaly detection Survey of Text Mining II offers a broad selection in state-of-the art algorithms and software for text mining from both academic and industrial perspectives, to generate interest and insight into the stateof the field. This book will be an indispensable resource for researchers, practitioners, and professionals involved in information retrieval, computational statistics, and data mining. Michael W. Berry is a professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville. Malu Castellanos is a senior researcher at Hewlett-Packard Laboratories in Palo Alto, California.
This book constitutes the thoroughly refereed conference proceedings of the 7th International Workshop on Business Intelligence for the Real-Time Enterprise, BIRTE 2013, held in Riva del Garda, Italy, in August 2013 and of the 8th International Workshop on Business Intelligence for the Real-Time Enterprise, BIRTE 2014, held in Hangzhou, China, in September 2014, in conjunction with VLDB 2013 and 2014, the International Conference on Very Large Data Bases. The BIRTE workshop series provides a forum for the discussion and advancement of the science and engineering enabling real-time business intelligence and the novel applications that build on these foundational techniques. This volume contains five full, two short, and two demo papers, which were carefully reviewed and selected with an acceptance rate of 45%. In addition, one keynote and three invited papers are included.
This book constitutes the thoroughly refereed conference proceedings of the 6th International Workshop on Business Intelligence for the Real-Time Enterprise, BIRTE 2012, held in Istanbul, Turkey, in August 2012, in conjunction with VLDB 2012, the International Conference on Very Large Data Bases. The BIRTE workshop series provides a forum to discuss and advance the science and engineering enabling real-time business intelligence and the novel applications that build on these foundational techniques. This volume contains 10 research papers, which have been carefully reviewed and selected from xx submissions.
This book constitutes the thoroughly refereed conference proceedings of the 5th International Workshop on Business Intelligence for the Real-Time Enterprise, BIRTE 2011, held in Seattle, WA, USA, in September 2011, in conjunction with VLDB 2011, the International Conference on Very Large Data Bases. The series of BIRTE workshops aims to provide a forum for researchers to discuss and advance the foundational science and engineering required to enable real-time business intelligence as well as novel applications and solutions based on these foundational techniques.The volume contains 6 research papers, which have been carefully reviewed and selected from 12 submissions, plus the 3 keynotes presented at the workshop. The topics cover all stages of the business intelligence cycle, including capturing of real-time data, handling of temporal or uncertain data, performance issues, event management, and the optimization of complex ETL workflows. The volume contains 6 research papers, which have been carefully reviewed and selected from 12 submissions, plus the 3 keynotes presented at the workshop. The topics cover all stages of the business intelligence cycle, including capturing of real-time data, handling of temporal or uncertain data, performance issues, event management, and the optimization of complex ETL workflows.
This Second Edition brings readers thoroughly up to date with the emerging field of text mining, the application of techniques of machine learning in conjunction with natural language processing, information extraction, and algebraic/mathematical approaches to computational information retrieval. The book explores a broad range of issues, ranging from the development of new learning approaches to the parallelization of existing algorithms. Authors highlight open research questions in document categorization, clustering, and trend detection. In addition, the book describes new application problems in areas such as email surveillance and anomaly detection.
In todayis competitive and highly dynamic environment, analyzing data to understand how the business is performing, to predict outcomes and trends, and to improve the effectiveness of business processes underlying business operations has become cri- cal. The traditional approach to reporting is no longer adequate, users now demand easy-to-use intelligent platforms and applications capable of analyzing real-time bu- ness data to provide insight and actionable information at the right time. The end goal is to improve the enterprise performance by better and timelier decision making, - abled by the availability of up-to-date, high-quality information. As a response, the notion of "real-time enterprise" has emerged and is beginning to be recognized in the industry. Gartner defines it as "using up-to-date information, getting rid of delays, and using speed for competitive advantage is what the real-time enterprise is all about. . . Indeed, the goal of the real-time enterprise is to act on events as they happen. " Although there has been progress in this direction and many com- nies are introducing products toward making this vision a reality, there is still a long way to go. In particular, the whole lifecycle of business intelligence requires new techniques and methodologies capable of dealing with the new requirements imposed by the real-time enterprise."
This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Business Intelligence for the Real-Time Enterprise, BIRTE 2006, held in Seoul, Korea in September 2006 in conjunction with VLDB 2006, the International Conference on Very Large Data Bases. The papers discuss the five major aspects of business intelligence for the real-time enterprise.
This book constitutes the thoroughly refereed conference proceedings of the BIRTE workshops listed below, which were held in in conjunction with VLDB, the International Conference on Very Large Data Bases: 9th International Workshop on Business Intelligence for the Real-Time Enterprise, BIRTE 2015, held in Kohala Coast, Hawaii, in August 2015, 10th International Workshop on Enabling Real-Time Business Intelligence, BIRTE 2016, held in New Delhi, India, in September 2016, 11th International Workshop on Real-Time Business Intelligence and Analytics, BIRTE 2017, held in Munich, Germany, in August 2017. The BIRTE workshop series provides a forum for the discussion and advancement of the science and engineering enabling real-time business intelligence and the novel applications that build on these foundational techniques. The book includes five selected papers from BIRTE 2015; five selected papers from BIRTE 2016; and three selected papers from BIRTE 2017.
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