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This book relates the success of a seemingly impossible challenge: to have a group of academics and people living in persistent poverty conduct research together. What conditions can the knowledge drawn from poverty cross with academic rigor? What type of knowledge does this collaboration result in? This is what The Merging of Knowledge presents in terms of the processes of The Fourth World-University program and the result of its five groups of work: history, family, knowledge, work and human activity, and citizenship. The results featured in this book can be appreciated on many levels. At the level of content, this unique collaboration offers knowledge from the very poor regarding their lives that is neglected or misunderstood in fields as varied as history, family sociology, work sociology, and political science. This "voice of the voiceless" is brought to the book by collaborative writing and is presented with the academics' methodological and epistemological contribution. At the level of gathering and understanding the information collected, the very poor are often given the role as "witnesses" of poverty in interviews. Here, as researchers, they contribute to rigorously examined content that illuminates their situations.
Science is a left-brained subject. It sees the world in mathematical models. It is all built on logic. Religion is a right-brained subject. It sees the world in associations. It is all built on symbolism. Misconceptions are what prevent us from reconciling the associations with the mathematical models. Once the misconceptions are revealed, the problem goes away. The teachings of Eastern Philosophy are interwoven throughout the Old and New Testaments. What they have to say explains a great deal about what the Holy Bible is trying to say to us. It reveals much of the symbolism used in religion so that it can be understood. It takes you beyond the realm of faith and into the realm of knowing. The Mayan Calendar and its apparent connection to end-time prophecy is also reviewed. The evolution of consciousness that it reveals is leading us on a very definite path. Taken collectively, evolution, split brain, Eastern Philosophy, Christianity, and the Mayan Calendar are interwoven to present a worldview that is equally fascinating and very promising.
An ideal text for researchers and professionals alike, this book constitutes the refereed proceedings of the 5th International Symposium on Foundations of Information and Knowledge Systems, FoIKS 2008 held in Pisa, Italy, in February 2008. The 13 revised full papers are presented together with nine revised short papers and three invited lectures. All of these were carefully selected during two rounds of reviewing and improvement from a total of 79 submissions.
When I ?rst came across the term data mining and knowledge discovery in databases, I was excited and curious to ?nd out what it was all about. I was excited because the term tends to convey a new ?eld that is in the making. I was curious because I wondered what it was doing that the other ?elds of research, such as statistics and the broad ?eld of arti?cial intelligence, were not doing. After reading up on the literature, I have come to realize that it is not much different from conventional data analysis. The commonly used de?nition of knowledge discovery in databases: “the non-trivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data” is actually in line with the core mission of conventional data analysis. The process employed by conventional data analysis is by no means trivial, and the patterns in data to be unraveled have, of course, to be valid, novel, useful and understandable. Therefore, what is the commotion all about? Careful scrutiny of the main lines of research in data mining and knowledge discovery again told me that they are not much different from that of conventional data analysis. Putting aside data warehousing and database m- agement aspects, again a main area of research in conventional database research, the rest of the tasks in data mining are largely the main concerns of conventional data analysis.
Researchers and professionals
The LNCS journal Transactions on Large-scale Data and Knowledge-centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing (e.g. computing resources, services, metadata, data sources) across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. This, the 53rd issue of Transactions on Large-scale Data and Knowledge-centered Systems, contains six fully revised selected regular papers. Topics covered include time series management from edge to cloud, segmentation for time series representation, similarity research, semantic similarity in a taxonomy, linked data semantic distance, linguistics-informed natural language processing, graph neural network, protected features, imbalanced data, causal consistency in distributed databases, actor model, and elastic horizontal scalability.
This book addresses key issues during the creation of corporate strategy and M&A strategy by explaining how to define a complete and consistent strategy, use an all-encompassing scope for the strategy to avoid blind spots, include ecosystem and platform strategy, define M&A strategy and its exact relationships to corporate strategy, and how to define strategic fit of two companies. It also lays the foundation for a data-driven strategy.
A new turn in mixed methods research is here: merged methods. This provocative book offers a novel analysis of current mixed methods research, complicating traditional approaches and challenging existing techniques. Moving beyond the binary quantitative-qualitative distinction, the book presents methodologically grounded ways to merge methods in social research and integrate interpretive and structural approaches in one instrument or procedure. The book: Considers the importance of merging both epistemologies and methodologies. Showcases eight merged methods research approaches, from the Delphi method to multimodal content analysis. Explores the opportunities for merging methods using computational techniques, such as text mining. This innovative book is a must-read for any postgraduate student or researcher across the social sciences wanting to develop their understanding of mixed methods research.
"This evidence-based book provides the framework and guidelines that professionals need for working with the contemporary explosion of data that is creating opportunities and challenges to all phases of our society and commerce." –Larry R. Medsker, Research Professor in Physics and Data Science, The George Washington University Knowledge Management in Practice is a resource on how knowledge management (KM) is implemented. It provides specific KM methods, tips, techniques, and best practices to gain competitive advantage and the most from investing in KM. It examines how KM is leveraged by first responders, the military, healthcare providers, insurance and financial services companies, legal firms, human resources departments, merger and acquisition (M&A) firms, and research institutions. Essential KM concepts are explored not only from a foundational perspective but also from a practical application. These concepts include capturing and codifying tacit and explicit knowledge, KM methods, information architecture, search, KM and social media, KM and Big Data, and the adoption of KM. Readers can visit the book’s companion website, KM Mentor (www.KMMentor.com), where they can access: Presentations by industry leaders on a variety of topics KM templates and instruction on executing KM strategy, performing knowledge transfer, and KM assessments and audits KM program and project implementation guidance Insights and reviews on KM tools Guidance on implementing and executing various KM Methods Specialized KM publications A private secure collaboration community for members to discuss ideas and get expert answers and advice