Web Data Mining

Author: Bing Liu
Publisher: Springer Science & Business Media
ISBN: 9783642194603
Format: PDF, Kindle
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Liu has written a comprehensive text on Web mining, which consists of two parts. The first part covers the data mining and machine learning foundations, where all the essential concepts and algorithms of data mining and machine learning are presented. The second part covers the key topics of Web mining, where Web crawling, search, social network analysis, structured data extraction, information integration, opinion mining and sentiment analysis, Web usage mining, query log mining, computational advertising, and recommender systems are all treated both in breadth and in depth. His book thus brings all the related concepts and algorithms together to form an authoritative and coherent text. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in Web mining and data mining both as a learning text and as a reference book. Professors can readily use it for classes on data mining, Web mining, and text mining. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.

A User Acceptance of Web Personalization Systems

Author: Dr. Fendi Ameen
Publisher: Iris Publishing
ISBN:
Format: PDF, ePub, Mobi
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Research on web personalization techniques for collecting and analysing web data in order to deliver personalized information to users is in an advanced state. Many metrics from the computational intelligence field have been developed to evaluate the algorithmic performance of Web Personalization Systems (WPSs). However, measuring the success of a WPS in terms of user acceptance is difficult until the WPS is deployed in practice. In summary, many techniques exist for delivering personalized information to a user, but a comprehensive measure of the success in WPSs in terms of human interaction and behaviour does not exist. This study aims to develop a framework for measuring user acceptance of WPSs from a user perspective. The proposed framework is based on the unified theory of acceptance and use of technology (UTAUT). The antecedents of user accep- tance are described by indicators based on four key constructs, i.e. performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC). All these constructs are underpinned by Information Systems (IS) theories that determine the intention to use (BI) and the actual use (USE) of a technology. A user acceptance model was proposed and validated using structural equation modelling (SEM) via the partial least squares path modelling (PLS-PM). Four user characteristics (i.e. gender, age, skill and experience) have been chosen for testing the moderating effects of the four constructs. The relationship between the four constructs in regard to BI and USE has been validated through moderating effects, in order to present an overall view of the extent of user acceptance of a WPS. Results from response data analysis show that the acceptance of a WPS is deter- mined through PE, EE SI, and FC. The gender of a user was found to moderate the relationship between performance expectancy of a WPS and their behavioural intention in using a WPS. The effect of behavioural intention on the use of WPS is higher for a group of females than for males. Furthermore, the proposed model has been tested and validated for its explanation power of the model and effect size. The current study concluded that predictive relevance of intention to use a WPS is more effective than the actual WPS usage, which indicated that intention to use has more prediction power for describing a user acceptance of a WPS. The implications of these measures from the computational intelligent point of view are useful when a WPS is implemented. For example, the designer of a WPS should consider personalized design features that enable the delivery of relevant information, sharing to other users, and accessibility across many platforms, Such features create a better web experience and a complete security policy. These measures can be utilized to obtain a higher attention rate and continued use by a user; the features that define user acceptance of a WPS.

Integration of Data Mining in Business Intelligence Systems

Author: Azevedo, Ana
Publisher: IGI Global
ISBN: 1466664789
Format: PDF, ePub
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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.

Data Quality

Author: Carlo Batini
Publisher: Springer Science & Business Media
ISBN: 3540331735
Format: PDF, ePub
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Poor data quality can seriously hinder or damage the efficiency and effectiveness of organizations and businesses. The growing awareness of such repercussions has led to major public initiatives like the "Data Quality Act" in the USA and the "European 2003/98" directive of the European Parliament. Batini and Scannapieco present a comprehensive and systematic introduction to the wide set of issues related to data quality. They start with a detailed description of different data quality dimensions, like accuracy, completeness, and consistency, and their importance in different types of data, like federated data, web data, or time-dependent data, and in different data categories classified according to frequency of change, like stable, long-term, and frequently changing data. The book's extensive description of techniques and methodologies from core data quality research as well as from related fields like data mining, probability theory, statistical data analysis, and machine learning gives an excellent overview of the current state of the art. The presentation is completed by a short description and critical comparison of tools and practical methodologies, which will help readers to resolve their own quality problems. This book is an ideal combination of the soundness of theoretical foundations and the applicability of practical approaches. It is ideally suited for everyone – researchers, students, or professionals – interested in a comprehensive overview of data quality issues. In addition, it will serve as the basis for an introductory course or for self-study on this topic.

Data Mining

Author: Bhavani Thuraisingham
Publisher: CRC Press
ISBN: 1482252503
Format: PDF, Docs
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Focusing on a data-centric perspective, this book provides a complete overview of data mining: its uses, methods, current technologies, commercial products, and future challenges. Three parts divide Data Mining: Part I describes technologies for data mining - database systems, warehousing, machine learning, visualization, decision support, statistics, parallel processing, and architectural support for data mining Part II presents tools and techniques - getting the data ready, carrying out the mining, pruning the results, evaluating outcomes, defining specific approaches, examining a specific technique based on logic programming, and citing literature and vendors for up-to-date information Part III examines emerging trends - mining distributed and heterogeneous data sources; multimedia data, such as text, images, video; mining data on the World Wide Web; metadata aspects of mining; and privacy issues. This self-contained book also contains two appendices providing exceptional information on technologies, such as data management, and artificial intelligence. Is there a need for mining? Do you have the right tools? Do you have the people to do the work? Do you have sufficient funds allocated to the project? All these answers must be answered before embarking on a project. Data Mining provides singular guidance on appropriate applications for specific techniques as well as thoroughly assesses valuable product information.

Web Technologies

Author: Arthur Tatnall
Publisher: IGI Global Snippet
ISBN: 1605669822
Format: PDF, Docs
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With the technological advancement of mobile devices, social networking, and electronic services, Web technologies continues to play an ever-growing part of the global way of life, incorporated into cultural, economical, and organizational levels. Web Technologies: Concepts, Methodologies, Tools, and Applications (4 Volume) provides a comprehensive depiction of current and future trends in support of the evolution of Web information systems, Web applications, and the Internet. Through coverage of the latest models, concepts, and architectures, this multiple-volume reference supplies audiences with an authoritative source of information and direction for the further development of the Internet and Web-based phenomena.

Artificial Immune Systems

Author: Scotland) ICARIS 2003 (2003 : Edinburgh
Publisher: Springer Science & Business Media
ISBN: 9783540407669
Format: PDF, Docs
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This book constitutes the refereed proceedings of the Second International Conference on Artificial Immune Systems, ICARIS 2003, held in Edinburgh, UK in September 2003. The 27 revised full papers presented were carefully reviewed and selected from 41 submissions. The book presents the first coherent account of the state of the art in artificial immune systems reserch. The papers are organized in topical sections on applications of artificial immune systems, immunocomputing, emerging metaphors, augmentation of artificial immune systems algorithms, theory of artificial immune systems, and representations and operators.

Transportation and Information

Author: Piyushimita Vonu Thakuriah
Publisher: Springer
ISBN:
Format: PDF, ePub, Docs
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Transformations in wireless connectivity and location-aware technologies hold the promise of bringing a sea-change in the way transportation information is generated and used in the future. Sensors in the transportation system, when integrated with those in other sectors (for example, energy, utility and health) have the potential to foster novel new ways of improving livability and sustainability. The end-result of these developments has been somewhat contradictory. Although automation in the transportation environment has become increasingly widespread, the level of involvement and active participation by people, in terms of co-creation and contribution of information, has also increased. As a result, the following two major trends have been observed: (1) increases in Machine-to- Machine (M2M) communications; and (2) increases in the variety and volume of User-Generated Content. In this transportation paradigm, the pervasive use of Information and Communication Technologies will serve as the foundation for mobility intelligence towards an “ubiquitous information-centered mobility environment”. However, many technical and operational questions, as well as social, management and legal challenges present themselves in the transformation to this vision. The book presents a non-technical review of research and initiatives and a discussion of such opportunities and challenges.

Database and Expert Systems Applications

Author: Qiming Chen
Publisher: Springer
ISBN: 3319228498
Format: PDF, ePub, Mobi
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This two volume set LNCS 9261 and LNCS 9262 constitutes the refereed proceedings of the 26th International Conference on Database and Expert Systems Applications, DEXA 2015, held in Valencia, Spain, September 1-4, 2015. The 40 revised full papers presented together with 32 short papers, and 2 keynote talks, were carefully reviewed and selected from 125 submissions. The papers discuss a range of topics including: temporal, spatial and high dimensional databases; semantic Web and ontologies; modeling, linked open data; NoSQLm NewSQL, data integration; uncertain data and inconsistency tolerance; database system architecture; data mining, query processing and optimization; indexing and decision support systems; modeling, extraction, social networks; knowledge management and consistency; mobility, privacy and security; data streams, Web services; distributed, parallel and cloud databases; information retrieval; XML and semi-structured data; data partitioning, indexing; data mining, applications; WWW and databases; data management algorithms. These volumes also include accepted papers of the 8th International Conference on Data Management in Cloud, Grid and P2P Systems, Globe 2015, held in Valencia, Spain, September 2, 2015. The 8 full papers presented were carefully reviewed and selected from 13 submissions. The papers discuss a range of topics including: MapReduce framework: load balancing, optimization and classification; security, data privacy and consistency; query rewriting and streaming.

Data Matching

Author: Peter Christen
Publisher: Springer Science & Business Media
ISBN: 3642311644
Format: PDF, Mobi
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Data matching (also known as record or data linkage, entity resolution, object identification, or field matching) is the task of identifying, matching and merging records that correspond to the same entities from several databases or even within one database. Based on research in various domains including applied statistics, health informatics, data mining, machine learning, artificial intelligence, database management, and digital libraries, significant advances have been achieved over the last decade in all aspects of the data matching process, especially on how to improve the accuracy of data matching, and its scalability to large databases. Peter Christen’s book is divided into three parts: Part I, “Overview”, introduces the subject by presenting several sample applications and their special challenges, as well as a general overview of a generic data matching process. Part II, “Steps of the Data Matching Process”, then details its main steps like pre-processing, indexing, field and record comparison, classification, and quality evaluation. Lastly, part III, “Further Topics”, deals with specific aspects like privacy, real-time matching, or matching unstructured data. Finally, it briefly describes the main features of many research and open source systems available today. By providing the reader with a broad range of data matching concepts and techniques and touching on all aspects of the data matching process, this book helps researchers as well as students specializing in data quality or data matching aspects to familiarize themselves with recent research advances and to identify open research challenges in the area of data matching. To this end, each chapter of the book includes a final section that provides pointers to further background and research material. Practitioners will better understand the current state of the art in data matching as well as the internal workings and limitations of current systems. Especially, they will learn that it is often not feasible to simply implement an existing off-the-shelf data matching system without substantial adaption and customization. Such practical considerations are discussed for each of the major steps in the data matching process.