Organizations generate and collect large volumes of textual data. Unfortunately, many companies are unable to capitalize fully on the value of this data because information implicit within it is not easy to discern. Primarily intended for business analysts and statisticians across multiple industries, this book provides an introduction to the types of problems encountered and current available text mining solutions.
This book constitutes the refereed proceedings of the 28th European Conference on Information Retrieval Research, ECIR 2006, held in London, April 2006. The 37 revised full papers and 28 revised poster papers presented are organized in topical sections on formal models, document and query representation and text understanding, topic identification and news retrieval, clustering and classification, refinement and feedback, performance and peer-to-peer networks, Web search, cross-language retrieval, genomic IR, and much more.
This book explores the technical, social and cultural implications of the emerging Information and communication technologies, addressing the technological and scientific development within education, commerce, governance, and security with a special emphasis on the impact on individuals, culture and society. Bringing together papers from the Second International Conference on Advances in Education, Commerce & Governance: Technology's Impact on Individuals, Culture and Society, the text will be of interest to researchers and academics working in areas related to the social, psychological and cultural impact of information communications technology (ICT). Specifically the book addresses a wide range of topics as diverse as: E-Commerce and E-Governance; Data and Information Privacy; Psychology; Gender; Culture; New Learning.
"This book provides the most recent technical information related to the computational models of the text mining process, discussing techniques within the realms of classification, association analysis, information extraction, and clustering. Offering an innovative approach to the utilization of textual information mining to maximize competitive advantage, it will provide libraries with the defining reference on this topic"--Provided by publisher.
Mobile agents are intelligent agents with advanced mobility capabilities. A mobile agent must be provided with the so called strong mobility, a feature which allows it to carry its status with it and accomplish its mission by migrating from site to site in the Internet. A mobile agent can complete in a site what it started in another site.Starting from the mobile agent concept, this book provides the reader with a suitably detailed discussion on mobile agent principles of operation, as for instance, migration, communication, co-ordination, interoperability, fault tolerance and security. As an example of mobile agents application fields, this book discusses how they can be effective in implementing data mining and information retrieval systems.
Bringing together papers presented at the ninth International Conference on Data Mining, this book addresses the developments in this important field. Featured topics include: data preparation, clustering technologies, customer relationship management, text mining, web mining, and categorisation methods.
Managing Complexity is the first book that clearly defines the concept of Complexity, explains how Complexity can be measured and tuned, and describes the seven key features of Complex Systems: ConnectivityAutonomyEmergencyNonequilibriumNon-linearitySelf-organisationCo-evolution The thesis of the book is that complexity of the environment in which we work and live offers new opportunities and that the best strategy for surviving and prospering under conditions of complexity is to develop adaptability to perpetually changing conditions. An effective method for designing adaptability into business processes using multi-agent technology is presented and illustrated by several extensive examples, including adaptive, real-time scheduling of taxis, see-going tankers, road transport, supply chains, railway trains, production processes and swarms of small space satellites. Additional case studies include adaptive servicing of the International Space Station; adaptive processing of design changes of large structures such as wings of the largest airliner in the world; dynamic data mining, knowledge discovery and distributed semantic processing. Finally, the book provides a foretaste of the next generation of complex issues, notably, The Internet of Things, Smart Cities, Digital Enterprises and Smart Logistics.
This book introduces text analytics as a valuable method for deriving insights from text data. Unlike other text analytics publications, Practical Text Analytics: Maximizing the Value of Text Data makes technical concepts accessible to those without extensive experience in the field. Using text analytics, organizations can derive insights from content such as emails, documents, and social media. Practical Text Analytics is divided into five parts. The first part introduces text analytics, discusses the relationship with content analysis, and provides a general overview of text mining methodology. In the second part, the authors discuss the practice of text analytics, including data preparation and the overall planning process. The third part covers text analytics techniques such as cluster analysis, topic models, and machine learning. In the fourth part of the book, readers learn about techniques used to communicate insights from text analysis, including data storytelling. The final part of Practical Text Analytics offers examples of the application of software programs for text analytics, enabling readers to mine their own text data to uncover information.
