Advances in Web Intelligence and Data Mining

Advances in Web Intelligence and Data Mining
Author: Mark Last
Publisher: Springer
Total Pages: 350
Release: 2006-08-11
Genre: Computers
ISBN: 3540338802

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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 Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining
Author: Usama M. Fayyad
Publisher:
Total Pages: 638
Release: 1996
Genre: Computers
ISBN:

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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.

Advances in Web Intelligence

Advances in Web Intelligence
Author: Janusz Kacprzyk
Publisher: Springer Science & Business Media
Total Pages: 529
Release: 2005-05-30
Genre: Computers
ISBN: 3540262199

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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 Web Intelligence and Data Mining. Studies in Computational Intelligence

Advances in Web Intelligence and Data Mining. Studies in Computational Intelligence
Author: Abraham Kandel
Publisher:
Total Pages:
Release: 2006
Genre:
ISBN:

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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

Advances in Web Intelligence
Author: Ernestina Menasalvas
Publisher: Springer Science & Business Media
Total Pages: 362
Release: 2003-04-28
Genre: Computers
ISBN: 3540401245

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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%.

Integration of Data Mining in Business Intelligence Systems

Integration of Data Mining in Business Intelligence Systems
Author: Azevedo, Ana
Publisher: IGI Global
Total Pages: 340
Release: 2014-09-30
Genre: Computers
ISBN: 1466664789

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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.

Advanced Techniques in Web Intelligence -1

Advanced Techniques in Web Intelligence -1
Author: Juan D. Velásquez
Publisher: Springer Science & Business Media
Total Pages: 278
Release: 2010-09-15
Genre: Computers
ISBN: 3642144608

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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.

Advances in Data Science and Analytics

Advances in Data Science and Analytics
Author: M. Niranjanamurthy
Publisher: John Wiley & Sons
Total Pages: 356
Release: 2022-12-08
Genre: Computers
ISBN: 111979188X

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Data science is an inter-disciplinary 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.

Advances in Data Mining

Advances in Data Mining
Author: Petra Perner
Publisher: Springer Science & Business Media
Total Pages: 115
Release: 2002-08-21
Genre: Business & Economics
ISBN: 3540441166

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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.

Integration Challenges for Analytics, Business Intelligence, and Data Mining

Integration Challenges for Analytics, Business Intelligence, and Data Mining
Author: Azevedo, Ana
Publisher: IGI Global
Total Pages: 250
Release: 2020-12-11
Genre: Computers
ISBN: 1799857832

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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.