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Articles 601 - 630 of 2694
Full-Text Articles in Computer Sciences
Using Social Influence To Predict Subscriber Churn, Derek Doran, Veena Mendiratta, Chitra Phadke, Dan Kushnir, Huseyin Uzunalioglu
Using Social Influence To Predict Subscriber Churn, Derek Doran, Veena Mendiratta, Chitra Phadke, Dan Kushnir, Huseyin Uzunalioglu
Kno.e.sis Publications
The saturation of mobile phone markets has resulted in rising costs for operators to obtain new customers. These operators thus focus their energies on identifying users that will churn so they can be targeted for retention campaigns. Typical churn prediction algorithms identify churners based on service usage metrics, network performance indicators, and demographic information. Social and peer-influence to churn, however, is usually not considered. In this paper, we describe a new churn prediction algorithm that incorporates the influence churners spread to their social peers. Using data from a major service provider, we show that social influence improves churn prediction and …
Understanding User Triads On Facebook, Derek Doran, Alberta De La Rosa Algarin, Swapna S. Gokhale
Understanding User Triads On Facebook, Derek Doran, Alberta De La Rosa Algarin, Swapna S. Gokhale
Kno.e.sis Publications
Contemporary approaches that analyze user behavior on online social networks only consider interactions among dyads, which are pairs of directly connected users. A large body of sociological work, however, suggests that mutual connections among users can influence their activities, leading to differences between two- and three-way interactions. This paper explores the dynamics of triads among Facebook users based on the wall posts from the New Orleans regional network. Initially, each connection is categorized as a close friendship or an acquiantance, contingent on the number of wall posts exchanged. Subsequently, the impact of different types of connections comprising triads is examined …
How I Would Like Semantic Web To Be, For My Children., Raghava Mutharaju
How I Would Like Semantic Web To Be, For My Children., Raghava Mutharaju
Kno.e.sis Publications
Semantic Web, since its inception, has gone through lot of developments in its relatively nascent existence; right from people's perception, to the standards and to its adoption by the industry and more importantly by the scientific community. This impressive growth only seems to increase. In this paper, we project this growth to the next 10 years and highlight some of the facets on which Semantic Web could have a major impact on. We also present the challenges that Semantic Web and its community has to deal with in order to get there.
An Efficient Bit Vector Approach To Semantics-Based Machine Perception In Resource-Constrained Devices, Cory Andrew Henson, Krishnaprasad Thirunarayan, Amit P. Sheth
An Efficient Bit Vector Approach To Semantics-Based Machine Perception In Resource-Constrained Devices, Cory Andrew Henson, Krishnaprasad Thirunarayan, Amit P. Sheth
Kno.e.sis Publications
The primary challenge of machine perception is to define efficient computational methods to derive high-level knowledge from low-level sensor observation data. Emerging solutions are using ontologies for expressive representation of concepts in the domain of sensing and perception, which enable advanced integration and interpretation of heterogeneous sensor data. The computational complexity of OWL, however, seriously limits its applicability and use within resource-constrained environments, such as mobile devices. To overcome this issue, we employ OWL to formally define the inference tasks needed for machine perception – explanation and discrimination – and then provide efficient algorithms for these tasks, using bit-vector encodings …
Towards Logical Linked Data Compression, Amit Krishna, Pascal Hitzler, Guozhu Dong
Towards Logical Linked Data Compression, Amit Krishna, Pascal Hitzler, Guozhu Dong
Computer Science and Engineering Faculty Publications
Linked data has experienced accelerated growth in recent years. With the continuing proliferation of structured data, demand for RDF compression is becoming increasingly important. In this study, we introduce a novel lossless compression technique for RDF datasets, called Rule Based compression (RB compression) that compresses datasets by generating a set of new logical rules from the dataset and removing triples that can be inferred from these rules. We employ existing frequent pattern mining algorithms for generating new logical rules. Unlike other compression techniques, our approach not only takes advantage of syntactic verbosity and data redundancy but also utilizes intra- and …
Iexplore: Interactive Browsing And Exploring Biomedical Knowledge, Vinh Nguyen, Olivier Bodenreider, Jagannathan Srinivasan, Todd Minning, Thomas Rindflesch, Bastien Rance, Ramakanth Kavuluru, Himi Yalamanchili, Krishnaprasad Thirunarayan, Satya S. Sahoo, Amit P. Sheth
Iexplore: Interactive Browsing And Exploring Biomedical Knowledge, Vinh Nguyen, Olivier Bodenreider, Jagannathan Srinivasan, Todd Minning, Thomas Rindflesch, Bastien Rance, Ramakanth Kavuluru, Himi Yalamanchili, Krishnaprasad Thirunarayan, Satya S. Sahoo, Amit P. Sheth
Kno.e.sis Publications
We present iExplore, a Semantic Web based application that helps biomedical researchers study and explore biomedical knowledge interactively. iExplore uses the Biomedical Knowledge Repository (BKR), which integrates knowledge from various sources ranging from information extracted from biomedical literature (from PubMed) to many structured vocabularies in the Unified Medical Language System (UMLS). The current version of BKR provides a unified provenance representation for 12 million semantic predications (triples with a predicate connecting a subject and an object) derived from 87 vocabulary families in the UMLS and 14 million predications extracted from 21 million PubMed abstracts. To engage the domain experts in …
Ceg 7900-01: Special Topics: Computer And Network Security, Junjie Zhang
Ceg 7900-01: Special Topics: Computer And Network Security, Junjie Zhang
Computer Science & Engineering Syllabi
This course will introduce active research topics in computer and network security, and will focus on discussing both sophisticated cyber-attacks and the defense mechanisms. The course will cover topics including intrusion detection, malware analysis, worm detection, botnet detection, spam, phishing, DNS security, web security, cellular network security, and privacy. This class is targeted at PhD and MS students who consider conducting research in computer and network security, and students who are interested in real-world security problems.
Ceg 4500/6500-01: Computer Graphics, Thomas Wischgoll
Ceg 4500/6500-01: Computer Graphics, Thomas Wischgoll
Computer Science & Engineering Syllabi
By the end of this quarter, you will have learnt techniques for constructing 2-D and 3·D objects as well as manipulating and rendering the objects using OpenGL.
The outline of the course is as follows:
•Introduction
•Geometric primitives
•Attributes of geometric primitives
•Antialiasing techniques
•Homogeneous coordinate system
•2-0 and 3-D viewing transformations
•Structures and hierarchical modeling
•Input devices and interactive techniques
•Visible surface detection methods
•Three-Dimensional Object Representations (chapter 8)
•Visible-Surface Detection (chapter 9)
•Illumination Models and Surface-Rendering Methods (chapter 10)
•Interactive Input Methods and Graphics User Interfaces (chapter 11)
•Color Models and Color Applications (chapter 12)
•Advanced Rendering and …
Computing Perception From Sensor Data, Payam Barnaghi, Frieder Ganz, Cory Andrew Henson, Amit P. Sheth
Computing Perception From Sensor Data, Payam Barnaghi, Frieder Ganz, Cory Andrew Henson, Amit P. Sheth
Kno.e.sis Publications
This paper describes a framework for perception creation from sensor data. We propose using data abstraction techniques, in particular Symbolic Aggregate Approximation (SAX), to analyse and create patterns from sensor data. The created patterns are then linked to semantic descriptions that define thematic, spatial and temporal features, providing highly granular abstract representation of the raw sensor data. This helps to reduce the size of the data that needs to be communicated from the sensor nodes to the gateways or highlevel processing components. We then discuss a method that uses abstract patterns created by SAX method and occurrences of different observations …
Privacy Preserving Boosting In The Cloud With Secure Half-Space Queries, Shumin Guo, Keke Chen
Privacy Preserving Boosting In The Cloud With Secure Half-Space Queries, Shumin Guo, Keke Chen
Kno.e.sis Publications
This paper presents a preliminary study on the PerturBoost approach that aims to provide efficient and secure classifier learning in the cloud with both data and model privacy preserved.
Cs 1010-01: Introduction To Computers And Office Productivity Software, Terri Bauer
Cs 1010-01: Introduction To Computers And Office Productivity Software, Terri Bauer
Computer Science & Engineering Syllabi
Focus on learning MS Office software applications including intermediate word processing, spreadsheets, database and presentation graphics using a case study approach where critical thinking and problem solving skills are required. Computer concepts are integrated throughout the course to provide an understanding of the basics of computing, the latest technological advances and how they are used in industry. Ethics and issues encountered in business are discussed to challenge students on societal impact of technology.
Cs 1150-01: Introduction To Computer Science, Karen Meyer
Cs 1150-01: Introduction To Computer Science, Karen Meyer
Computer Science & Engineering Syllabi
The Introduction to Computer Science course will expose students to the scientific method as implemented in computer science. The course will show students how the scientific method as implemented in computer science can be used as a problem-solving tool. The course requires students to apply and extend the concepts in a laboratory setting. The concepts will include the study of and methodology of algorithm discovery, design, application, and fundamentals of networks. Lecture and Lab
Cs 1160: Introduction To Computer Programming I, Vanessa Starkey
Cs 1160: Introduction To Computer Programming I, Vanessa Starkey
Computer Science & Engineering Syllabi
Basic concepts of computer programming with an emphasis on structured programming techniques. Includes an introduction to object-oriented programing. Integrated lecture/lab.
Cs 1160: Introduction To Computer Programming I, David M. Hutchison
Cs 1160: Introduction To Computer Programming I, David M. Hutchison
Computer Science & Engineering Syllabi
CS 1160 is the first in a sequence of two programming classes. This course will introduce students to the basic concepts of programming. Examples are from business applications with an emphasis on problem solving with the computer as a tool.
Cs 4800/6800: Web Information Systems, Amit P. Sheth
Cs 4800/6800: Web Information Systems, Amit P. Sheth
Computer Science & Engineering Syllabi
No abstract provided.
Cs 7800: Information Retrieval, Krishnaprasad Thirunarayan
Cs 7800: Information Retrieval, Krishnaprasad Thirunarayan
Computer Science & Engineering Syllabi
This course will cover models for information retrieval, techniques for indexing and searching. and algorithms for classification and clustering. It will also cover SVM, latent semantic indexing. link analysis and ranking, Map-Reduce architecture and Hadoop, to different degrees of detail, time permitting.
Cs/Mth 3260/5260: Numerical Methods For Computational Science, Ronald F. Taylor
Cs/Mth 3260/5260: Numerical Methods For Computational Science, Ronald F. Taylor
Computer Science & Engineering Syllabi
Numerical methods for the sciences using modern programming languages. Solution of linear and nonlinear equations, symmetric matrix eigenvalue problems, interpolation, and least squares. Initial value and boundary value problems for representative systems governed by ordinary and partial differential equations are also solved numerically. Three hours lecture.
Cs 3100/5100: Data Structures And Algorithms, Keke Chen
Cs 3100/5100: Data Structures And Algorithms, Keke Chen
Computer Science & Engineering Syllabi
This course will cover the fundamentals of algorithm design and analysis, the implementation of classical data structures and control structures, and the basic problem solving techniques.
Cs 1180-06: Computer Programming - I, Jay Dejongh
Cs 1180-06: Computer Programming - I, Jay Dejongh
Computer Science & Engineering Syllabi
Basic concepts of programming and programming languages are introduced. Emphasis is on problem solving and object oriented programming. This course provides a general introduction to the fundamentals of computer science and programming. Examples from and applications to a broad range of problems are given. No prior knowledge of programming is assumed. The concepts covered will be applied to the Java programming language. Students must register for both lecture and one laboratory section. 4 credit hours.
Cs 3190: Programming Language Workshop In Python, Krishnaprasad Thirunarayan
Cs 3190: Programming Language Workshop In Python, Krishnaprasad Thirunarayan
Computer Science & Engineering Syllabi
This course is designed as a self-study in Python. You are expected to learn the language and solve a set of programming problems assigned to you from Budd's Text using Python available from http://www.python.org. There are no exams. We officially meet only once in the quarter. However, l will be available in the posted office hours for clarifications and discussions about the programming problems.
Cs 3100/5100: Data Structures And Algorithms, Meilin Liu
Cs 3100/5100: Data Structures And Algorithms, Meilin Liu
Computer Science & Engineering Syllabi
This is a fundamental course for students majoring in Computer Science. Students will learn: basic algorithm analysis techniques; asymptotic complexity; big-0 and big-Omega notations; efficient algorithms for discrete structures including lists, trees, stacks, and graphs; fundamental computing algorithms including sorting, searching, and hashing techniques.
Cs 1200: Introduction To Discrete Structures, Pascal Hitzler
Cs 1200: Introduction To Discrete Structures, Pascal Hitzler
Computer Science & Engineering Syllabi
No abstract provided.
Cs 2800: Web Design Fundamentals, Mohamed B. Ali
Cs 2800: Web Design Fundamentals, Mohamed B. Ali
Computer Science & Engineering Syllabi
Introduction to basic web design, development, and information management. Topics include design principles, page layout, hierarchal organization, content management, use of color and graphics, privacy policies, accessibility and site organization. HTML, and modern web programming tools are included in the course.
Cs 1181: Computer Science Ii, Mateen M. Rizki
Cs 1181: Computer Science Ii, Mateen M. Rizki
Computer Science & Engineering Syllabi
This is the second course in a two-semester sequence introducing fundamental concepts and techniques for computer science and engineering. The course focuses on problem analysis, advanced programming concepts using JAVA and fundamental data structures. Students learn to analyze problems and evaluate potential solutions with respect to choice of data structures and computational efficiency. Student are exposed to the underlying implementation of basic data structures available in JAVA libraries and develop the skilled needs to extend existing data structures and design new data structures to solve increasingly complex problems.
Cs 4850/6850: Principles Of Artificial Intelligence, Shaojun Wang
Cs 4850/6850: Principles Of Artificial Intelligence, Shaojun Wang
Computer Science & Engineering Syllabi
No abstract provided.
Cs 2160: Visual Basic Programming, Eric Saunders
Cs 2160: Visual Basic Programming, Eric Saunders
Computer Science & Engineering Syllabi
This course will cover the fundamentals of object-oriented computer programming; with an emphasis on design, structure, debugging, and testing. Visual Basic 2010 will be used for developing programs.
Cs 7900: Information Security, Meilin Liu
Cs 7900: Information Security, Meilin Liu
Computer Science & Engineering Syllabi
This course gives a comprehensive study of security vulnerabilities in information systems and the basic techniques for developing secure applications and practicing safe computing. Topics include: Conventional encryption; Data Encryption Standard; Advanced Encryption Standard; Hashing functions and data integrity; Basic Number Theory; Public-key encryption (RSA); Digital signature; Security standards and applications; Access Control; Management and analysis of security. After taking this course, students will have the knowledge of several well-known security standards and their applications; and the students should be able to increase system security and develop secure applications.
Cs 3180/5180: Comparative Languages, Krishnaprasad Thirunarayan
Cs 3180/5180: Comparative Languages, Krishnaprasad Thirunarayan
Computer Science & Engineering Syllabi
This course will introduce fundamental concepts and paradigms underlying the design of modern programming languages. For concreteness, we study the details of an object-oriented language (e.g. Java, C#, C++), a functional language (e.g., Scheme, and get introduced to multiparadigm languages (e.g., Python, Scala). The overall goal is to enable comparison and evaluation of existing languages. The programming assignments will largely be coded in Java and in Scheme, and optionally in Python or Scala.
Cs 4000: Social Implications Of Computing, Leo Finkelstein
Cs 4000: Social Implications Of Computing, Leo Finkelstein
Computer Science & Engineering Syllabi
CS 4000 is a communication skills course using as its subject matter current salient issues associated with the social implications of computing. In addition to the course text, you will need to use certain reading materials in the library and elsewhere, and you will be responsible for using concepts and theories provided in class lectures and discussions.
Cs 7720: Data Mining, Guozhu Dong
Cs 7720: Data Mining, Guozhu Dong
Computer Science & Engineering Syllabi
This course studies the fundamental concepts, issues, and techniques of data mining. Topics include basics of data, data preprocessing, feature selection/extraction, frequent pattern and association/correlation mining, classification, clustering, outlier analysis, OLAP/OLAM, contrast mining, applications, etc.