الصفحة 2
الصفحة 2
Data Warehousing and Data Mining Techniques for Cyber Security
It provide techniques for collecting information from distributed databases and for performing data analysis. The ever expanding, tremendous amount of data collected and stored in large databases has far exceeded our human ability to comprehend--without the proper tools. There is a critical need for data analysis that can automatically analyze data, summarize it and predict future trends. In the modern age of Internet connectivity, concerns about denial of service attacks, computer viruses and worms are extremely important. Data Warehousing and Data Mining Techniques for Cyber Security contributes to the discipline of security informatics. The author discusses topics that intersect cyber security and data mining, while providing techniques for improving cyber security. Since the cost of information processing and internet accessibility is dropping, an increasing number of organizations are becoming vulnerable to cyber attacks. This volume introduces techniques for applications in the area of retail, finance, and bioinformatics, to name a few.
Data Mining : A Knowledge Discovery Approach
This book on data mining details the unique steps of the knowledge discovery process that prescribe the sequence in which data mining projects should be performed. Data Mining offers an authoritative treatment of all development phases from problem and data understanding through data preprocessing to deployment of the results. This knowledge discovery approach is what distinguishes this book from other texts in the area. It concentrates on data preparation, clustering and association rule learning (required for processing unsupervised data), decision trees, rule induction algorithms, neural networks, and many other data mining methods, focusing predominantly on those which have proven successful in data mining projects.
Data Management. Data, Data Everywhere ; 24th British National Conference on Databases, BNCOD 24, Glasgow, UK, July 3-5, 2007, Proceedings
One of the most pressing challenges is to ?nd ways of evolving database technology to cope with its new role in underpinning the massively distributed and heterogeneous applications built on top of the Internet. This has afiected both the ways in which data has been accessed and the ways in which it is represented, with XML data management becoming an important issue and, as such, heavily represented at this conference. It has also brought back issues of performance that might have been considered largely solved by the improvements in hardware, since data now has to be managed on devices of low power and small memory as well as on standard client and powerful server machines. We therefore invited papers on all aspects of data management, particularly related to how dataisused in the ubiquitous environment of the modern Internet by complex distributed and scientific applications.
Data Engineering Issues in E-Commerce and Services ; 2nd International Workshop, DEECS 2006, San Francisco, CA, USA, June 26, 2006
The purpose of the DEECS workshop is to provide an annual forum for exchange of state-of-the-art research and development in e-commerce and services. Since the increasing demand on e-commerce and services, we are witnessing a continuing growth of interest in the workshop. The increased number of submissions this year includes a record number from Asia.
Current trends in database technology - EDBT 2004 Workshops ; EDBT 2004 Workshops PhD, DataX, PIM, P2P&DB, and ClustWeb, Heraklion, Crete, Greece, March 14-18, 2004, Revised Selected Papers
This volume comprises papers from the following ?ve workshops that were part of the complete program for the International Conference on Extending Database Technology (EDBT) held in Heraklion, Greece, March 2004: • ICDE/EDBT Joint Ph. D. Workshop (PhD) • Database Technologies for Handling XML-information on the Web (DataX) • Pervasive Information Management (PIM) • Peer-to-Peer Computing and Databases (P2P&DB) • Clustering Information Over the Web (ClustWeb) Together, the ?ve workshops featured 61 high-quality papers selected from appr- imately 180 submissions.
Cooperative Design, Visualization, and Engineering ; 4th International Conference, CDVE 2007, Shanghai,China, September 16-20, 2007
The cooperative design, visualization and engineering community sensed the economic pulse of a new giant economy where cooperation is vital for its success. This year we received a large number of papers from all over the world.From a technical point of view, as a major trend in cooperative design, vi- alization, engineering and other applications, advanced Web-based cooperation technology stands out by itself. Web-based cooperative working applications have been emerging strongly since the wide availability and accessibility of the WWW. It is a form of sharing and collaborating by its nature.
Conceptual Modeling - ER 2007 ; 26th International Conference on Conceptual Modeling, Auckland, New Zealand, November 5-9, 2007, Proceedings
Conceptual modeling is fundamental to the development of complex systems, because it provides the key communication means between systems developers, end-users and customers.Conceptua lmodeling provides languages,methods and tools to understand and represent the application domain;to elicitate,concepalize and formalize system requirements and user needs;to communicate systems designs to all stakeholders; to formally verify and validate system designs on high levels of abstractions; and to minimize ambiguities in system development. Initially, conceptual modeling mainly addressed data-intensive information s- tems and contributed to data modeling and database application engineering. The area of conceptual modeling has now matured to encompass all kinds of application areas such as e-applications (including e-business and e-learning), web-based systems (including the semantic web and ubiquitous systems), life science and geographic applications.
Journal on Data Semantics XI
The LNCS Journal on Data Semantics is devoted to the presentation of notable work that, in one way or another, addresses research and development on issues related to data semantics. The scope of the journal ranges from theories supporting the formal definition of semantic content to innovative domain-specific applications of semantic knowledge. The journal addresses researchers and advanced practitioners working on the semantic web, interoperability, mobile information services, data warehousing, knowledge representation and reasoning, conceptual database modeling, ontologies, and artificial intelligence.
Journal on Data Semantics X
Web semantics and semi-structured data , Semantic caching , Data warehousing and semantic data mining , Spatial, temporal, multimedia and multimodal semantics , Semantics in data visualization , Semantic services for mobile users , Supporting tools , Applications of semantic-driven approaches These topics are to be understood as specifically related to semantic issues. Contributions submitted to the journal and dealing with semantics of data will be considered even if they are not from the topics in the list. While the physical appearance of the journal issues is like the books from the we- known Springer LNCS series, the mode of operation is that of a journal. Contributions can be freely submitted by authors and are reviewed by the Editorial Board.
Journal on Data Semantics VIII
Springer's LNCS Journal on Data Semantics aims at providing a highly visible dissemination channel for most remarkable work that in one way or another addresses research and development on issues related to the semantics of data. The target domain ranges from theories supporting the formal definition of semantic content to innovative domain-specific application of semantic knowledge. This publication channel should be of the highest interest to researchers and advanced practitioners working on the Semantic Web, interoperability, mobile information services, data warehousing, knowledge representation and reasoning, conceptual database modeling, ontologies, and artificial intelligence.
Journal on Data Semantics VII
The LNCS Journal on Data Semantics is devoted to the presentation of notable work that, in one way or another, addresses research and development on issues related to data semantics. Based on the highly visible publication platform Lecture Notes in Computer Science, this new journal is widely disseminated and available worldwide. The scope of the journal ranges from theories supporting the formal definition of semantic content to innovative domain-specific applications of semantic knowledge. The journal addresses researchers and advanced practitioners working on the semantic web, interoperability, mobile information services, data warehousing, knowledge representation and reasoning, conceptual database modeling, ontologies, and artificial intelligence.
Journal on Data Semantics VI
Data warehousing and semantic data mining • Spatial, temporal, multimedia and multimodal semantics • Semantics in data visualization • Semantic services for mobile users • Supporting tools • Applications of semantic-driven approaches These topics are to be understood as speci?cally related to semantic issues. Contributions submitted to the journal and dealing with semantics of data will be considered even if they are not within the topics in the list. While the physical appearanceof the journal issues looks like the books from the well-known Springer LNCS series, the mode of operation is that of a jo- nal. Contributions can be freely submitted by authors and are reviewed by the Editorial Board. Contributions may also be invited, and nevertheless carefully reviewed, as in the case for issues that contain extended versions of best papers from major conferences addressing data semantics issues. Special issues, foc- ing on a speci?c topic, are coordinated by guest editors once the proposal for a special issue is accepted by the Editorial Board.
Journal on Data Semantics V
The LNCS Journal on Data Semantics is devoted to the presentation of notable work that, in one way or another, addresses research and development on issues related to data semantics. Based on the highly visible publication platform Lecture Notes in Computer Science, this new journal is widely disseminated and available worldwide. The scope of the journal ranges from theories supporting the formal definition of semantic content to innovative domain-specific applications of semantic knowledge. The journal addresses researchers and advanced practitioners working on the semantic web, interoperability, mobile information services, data warehousing, knowledge representation and reasoning, conceptual database modeling, ontologies, and artificial intelligence.
Journal on Data Semantics IX
The LNCS Journal on Data Semantics is devoted to the presentation of notable work that, in one way or another, addresses research and development on issues related to data semantics. The scope of the journal ranges from theories supporting the formal definition of semantic content to innovative domain-specific applications of semantic knowledge.
Journal on Data Semantics III
– semantic caching – data warehousing and semantic data mining – spatial, temporal, multimedia and multimodal semantics – semantics in data visualization – semantic services for mobile users – supporting tools – applications of semantic-driven approaches These topics are to be understood as speci?cally related to semantic issues. Contributions submitted to the journal and dealing with semantics of data will be considered even if they are not within the topics in the list. While the physical appearance of the journal issues looks like the books from the well-known Springer LNCS series, the mode of operation is that of a journal. Contributions can be freely submitted by authors and are reviewed by the Editorial Board. Contributions may also be invited, and nevertheless carefully reviewed, as in the case for issues that contain extended versions of best papers from major conferences addressing data semantics issues. Special issues, focusing on a speci?c topic, are coordinated by guest editors once the proposal for a special issue is accepted by the Editorial Board. Finally, it is also possible that a journal issue be devoted to a single text.
Journal on Data Semantics II
The LNCS Journal on Data Semantics is devoted to the presentation of notable work that, in one way or another, addresses research and development on issues related to data semantics. Based on the highly visible publication platform Lecture Notes in Computer Science, this new journal is widely disseminated and available worldwide. The scope of the journal ranges from theories supporting the formal definition of semantic content to innovative domain-specific applications of semantic knowledge. The journal addresses researchers and advanced practitioners working on the semantic web, interoperability, mobile information services, data warehousing, knowledge representation and reasoning, conceptual database modeling, ontologies, and artificial intelligence.
Business Intelligence for the Real-Time Enterprises ; 1st International Workshop, BIRTE 2006, Seoul, Korea, September 11, 2006, Revised Selected Papers
The book includes different aspects in the lifecycle of business intelligence on very large enterprise-wide operational real-time data sets. In today’s competitive and highly dynamic environment, analyzing data to und- stand how the business is performing, to predict outcomes and trends, and to improve the effectiveness of business processes underlying business operations has become critical. The traditional approach to reporting is not longer adequate; users now - mand easy-to-use intelligent platforms and applications capable of analyzing real-time business data to provide insight and actionable information at the right time. The end goal is to improve the enterprise performance by better and timelier decision making, enabled by the availability of up-to-date, high-quality information.
Building a Data Warehouse : With Examples in SQL Server
The book is organized as follows. In the beginning of this book (chapters 1 through 6), you learn how to build a data warehouse, for example, defining the architecture, understanding the methodology, gathering the requirements, designing the data models, and creating the databases. Then in chapters 7 through 10, you learn how to populate the data warehouse, for example, extracting from source systems, loading the data stores, maintaining data quality, and utilizing the metadata. After you populate the data warehouse, in chapters 11 through 15, you explore how to present data to users using reports and multidimensional databases and how to use the data in the data warehouse for business intelligence, customer relationship management, and other purposes. Chapters 16 and 17 wrap up the book: After you have built your data warehouse, before it can be released to production, you need to test it thoroughly. After your application is in production, you need to understand how to administer data warehouse operation.
Beginning SQL Server 2008 for Developers : From novice to professional
SQL Server 2008 is a first–rate database management system. It offers more capability than any previous release of SQL Server. More than just a classic relational database management system, SQL Server 2008 includes exciting and powerful features that make it useful for everything from large corporate data warehouses to ad hoc departmental databases. You'll find enhanced support for XML, new support for spatial data, transparent data encryption, a policy–based management system, and more.
Anomaly Detection : Techniques and Applications
When information in the data warehouse is processed, it follows a definite pattern. An unexpected deviation in the data pattern from the usual behavior is called an anomaly. The anomaly in the data is also referred to as noise, outlier, spammer, deviations, novelties and exceptions. Identification of the rare items, events, observations, patterns which raise suspension by differing significantly from the majority of data is called anomaly detection. With progress in the technologies and the widespread use of data for the purpose for business the increase in the spams faced by the individuals and the companies are increasing day by day. This noisy data has boomed as a major problem in various areas such as Internet of Things, web service, Machine Learning, Artificial Intelligence, Deep learning, Image Processing, Cloud Computing, Audio processing, Video Processing, VoIP, Data Science, Wireless Sensor etc. Identifying the anomaly data and filtering them before processing is a major challenge for the data analyst. This anomaly is unavoidable in all areas of research. This book covers the techniques and algorithms for detecting the deviated data.
