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Advances in Web Intelligence and Data Mining by Mark Last,Piotr S. Szczepaniak,Zeev Volkovich,Abraham Kandel Pdf
This book presents state-of-the-art developments in the area of computationally intelligent methods applied to various aspects and ways of Web exploration and Web mining. Some novel data mining algorithms that can lead to more effective and intelligent Web-based systems are also described. Scientists, engineers, and research students can expect to find many inspiring ideas in this volume.
Advances in Web Intelligence and Data Mining. Studies in Computational Intelligence by Abraham Kandel,Mark Last,Piotr S. Szczepaniak,Zeev Volkovich Pdf
The Internet has become a major communication medium, where virtually any kind of content can be transferred instantly and reliably between individual users and entire organizations located in any part of the globe. Consequently, more effective and efficient methods and technologies are needed to make the most of the Web's nearly unlimited potential. The new Web-related research directions include intelligent methods usually associated with the fields of computational intelligence, soft computing, and data mining. This book presents state-of-the-art developments in the area of computationally intelligent methods applied to various aspects and ways of Web exploration and Web mining. Some novel data mining algorithms that can lead to more effective and intelligent Web-based systems are also described. Scientists, engineers, and research students are expected to find many inspiring ideas in this volume.
Advances in Web Intelligence by Janusz Kacprzyk,Piotr S. Szczepaniak Pdf
This book constitutes the refereed proceedings of the Third International Atlantic Web Intelligence Conference, AWIC 2005, held in Lodz, Poland in June 2005. The 74 revised papers presented together with abstracts of 4 invited papers were carefully reviewed and selected from 140 submissions. All current aspects Web intelligence are addressed including semantic Web issues, ambient intelligence, intelligent information services, Web search, distributed service management, clustering, visualization, data mining, description logics, ontologies, Web query processing, categorization, classification, Web services, e-learning, and knowledge discovery.
Advances in Knowledge Discovery and Data Mining by Usama M. Fayyad Pdf
Eight sections of this book span fundamental issues of knowledge discovery, classification and clustering, trend and deviation analysis, dependency derivation, integrated discovery systems, augumented database systems and application case studies. The appendices provide a list of terms used in the literature of the field of data mining and knowledge discovery in databases, and a list of online resources for the KDD researcher.
Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence by Trivedi, Shrawan Kumar,Dey, Shubhamoy,Kumar, Anil,Panda, Tapan Kumar Pdf
The development of business intelligence has enhanced the visualization of data to inform and facilitate business management and strategizing. By implementing effective data-driven techniques, this allows for advance reporting tools to cater to company-specific issues and challenges. The Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence is a key resource on the latest advancements in business applications and the use of mining software solutions to achieve optimal decision-making and risk management results. Highlighting innovative studies on data warehousing, business activity monitoring, and text mining, this publication is an ideal reference source for research scholars, management faculty, and practitioners.
Integration of Data Mining in Business Intelligence Systems by Azevedo, Ana Pdf
Uncovering and analyzing data associated with the current business environment is essential in maintaining a competitive edge. As such, making informed decisions based on this data is crucial to managers across industries. Integration of Data Mining in Business Intelligence Systems investigates the incorporation of data mining into business technologies used in the decision making process. Emphasizing cutting-edge research and relevant concepts in data discovery and analysis, this book is a comprehensive reference source for policymakers, academicians, researchers, students, technology developers, and professionals interested in the application of data mining techniques and practices in business information systems.
Integration Challenges for Analytics, Business Intelligence, and Data Mining by Azevedo, Ana,Santos, Manuel Filipe Pdf
As technology continues to advance, it is critical for businesses to implement systems that can support the transformation of data into information that is crucial for the success of the company. Without the integration of data (both structured and unstructured) mining in business intelligence systems, invaluable knowledge is lost. However, there are currently many different models and approaches that must be explored to determine the best method of integration. Integration Challenges for Analytics, Business Intelligence, and Data Mining is a relevant academic book that provides empirical research findings on increasing the understanding of using data mining in the context of business intelligence and analytics systems. Covering topics that include big data, artificial intelligence, and decision making, this book is an ideal reference source for professionals working in the areas of data mining, business intelligence, and analytics; data scientists; IT specialists; managers; researchers; academicians; practitioners; and graduate students.
Advances in Data Science and Analytics by M. Niranjanamurthy,Hemant Kumar Gianey,Amir H. Gandomi Pdf
ADVANCES in DATA SCIENCE and ANALYTICS Presenting the concepts and advances of data science and analytics, this volume, written and edited by a global team of experts, also goes into the practical applications that can be utilized across multiple disciplines and industries, for both the engineer and the student, focusing on machining learning, big data, business intelligence, and analytics. Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from many structural and unstructured data. Data science is related to data mining, deep learning, and big data. Data analytics software is a more focused version of this and can even be considered part of the larger process. Analytics is devoted to realizing actionable insights that can be applied immediately based on existing queries. For the purposes of this volume, data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines. While a data scientist is expected to forecast the future based on past patterns, data analysts extract meaningful insights from various data sources. Although data mining and other related areas have been around for a few decades, data science and analytics are still quickly evolving, and the processes and technologies change, almost on a day-to-day basis. This volume provides an overview of some of the most important advances in these areas today, including practical coverage of the daily applications. Valuable as a learning tool for beginners in this area as well as a daily reference for engineers and scientists working in these areas, this is a must-have for any library.
Advanced Techniques in Web Intelligence -1 by Juan D. Velásquez Pdf
This book introduces a research applications in Web intelligence. It presents a number of innovative proposals which will contribute to the development of web science and technology for the long-term future, rendering this work a valuable piece of knowledge.
Data Mining for Intelligence, Fraud & Criminal Detection by Christopher Westphal Pdf
In 2004, the Government Accountability Office provided a report detailing approximately 200 government-based data-mining projects. While there is comfort in knowing that there are many effective systems, that comfort isn’t worth much unless we can determine that these systems are being effectively and responsibly employed. Written by one of the most respected consultants in the area of data mining and security, Data Mining for Intelligence, Fraud & Criminal Detection: Advanced Analytics & Information Sharing Technologies reviews the tangible results produced by these systems and evaluates their effectiveness. While CSI-type shows may depict information sharing and analysis that are accomplished with the push of a button, this sort of proficiency is more fiction than reality. Going beyond a discussion of the various technologies, the author outlines the issues of information sharing and the effective interpretation of results, which are critical to any integrated homeland security effort. Organized into three main sections, the book fully examines and outlines the future of this field with an insider’s perspective and a visionary’s insight. Section 1 provides a fundamental understanding of the types of data that can be used in current systems. It covers approaches to analyzing data and clearly delineates how to connect the dots among different data elements Section 2 provides real-world examples derived from actual operational systems to show how data is used, manipulated, and interpreted in domains involving human smuggling, money laundering, narcotics trafficking, and corporate fraud Section 3 provides an overview of the many information-sharing systems, organizations, and task forces as well as data interchange formats. It also discusses optimal information-sharing and analytical architectures Currently, there is very little published literature that truly defines real-world systems. Although politics and other factors all play into how much one agency is willing to support the sharing of its resources, many now embrace the wisdom of that path. This book will provide those individuals with an understanding of what approaches are currently available and how they can be most effectively employed.
This book presents six thoroughly reviewed and revised full papers describing selected projects on data mining. Three papers deal with data mining and e-commerce, focusing on sequence rule analysis, association rule mining and knowledge discovery in databases, and intelligent e-marketing with Web mining. One paper is devoted to experience management and process learning. The last two papers report on medical applications, namely on genomic data processing and on case-based reasoning for prognosis of influenza.
Exploring Advances in Interdisciplinary Data Mining and Analytics: New Trends by Taniar, David,Iwan, Lukman Hakim Pdf
"This book is an updated look at the state of technology in the field of data mining and analytics offering the latest technological, analytical, ethical, and commercial perspectives on topics in data mining"--Provided by publisher.
Emergent Web Intelligence: Advanced Information Retrieval by Richard Chbeir,Youakim Badr,Ajith Abraham,Aboul-Ella Hassanien Pdf
This volume reviews cutting-edge technologies and insights related to XML-based and multimedia information access and data retrieval. And by applying new techniques to real-world scenarios, it details how organizations can gain competitive advantages.
Advances in Web Intelligence by Ernestina Menasalvas,Javier Segovia,Piotr S. Szczepaniak Pdf
We are pleased to present the proceedings of the 2003 Atlantic Web Intelligence C- ference, AWIC 2003. The conference was located in Madrid, Spain during May 5–6, 2003, organized locally by the Technical University of Madrid. AWIC 2003 aimed to be the rst of a series of conferences on Web Intelligence, to be celebrated annually, alternatively in Europe and America, starting in Madrid. It was born as an activity of the recently created WIC-Poland Research Centre and the WIC-Spain Research Centre, bothbelongingtotheWebIntelligenceConsortium(WIC) (http://wi-consortium.org).AWIC 2003 was supported with grants from the S- nish Ministry for Science and Technology and the European Network of Excellence in Knowledge Discovery, KDNet. AWIC 2003 brought together scientists, engineers, computer users, and students to exchange and share their experiences, new ideas, and research results about all aspects (theory,applications,andtools)ofarti cialintelligencetechniquesappliedtoWeb-based systems, and to discuss the practical challenges encountered and the solutions adopted. Almost 70 contributions were submitted. After a preliminary evaluation, 60 of these papers were accepted to the conference and were assigned at least two reviewers from the international program committee. Out of this 60, 33 were conditionally accepted, and 32 of them were nally accepted after the conditions set by the reviewers had been met, which resulted in an acceptance ratio of 45%.
Emergent Web Intelligence: Advanced Semantic Technologies by Youakim Badr,Richard Chbeir,Ajith Abraham,Aboul-Ella Hassanien Pdf
The success of the World Wide Web depends on the ability of users to store, p- cess and retrieve digital information regardless of distance boundaries, languages and domains of knowledge. The universality and ?exibility of the World Wide Web have also enabled the rapid growth of a variety of new services and applications based on human–machine interaction. The semantics of exchanged information and services should be useful not only for human to human communications, but also in that machines would be able to understand and automatically process web content. Semanticsgive well-de?nedmeaningto web content and enable computersand p- ple to work in cooperation. Today, the crucial challenge becomes the development of languages to express information in a machine processable format. Now more than ever, new advanced techniques and intelligent approaches are required to tra- form the Web into a universal reasoning and computing machine. Web intelligence attempts to deal with this challenge by exploiting information technologies and - ti?cial intelligence approaches to design the next generation of web-empowered systems and services.
