Analysis of Neighbourhoods in Multi-layered Dynamic Social Networks

Social networks existing among employees, customers or users of various IT systems have become one of the research areas of growing importance. A social network consists of nodes - social entities and edges linking pairs of nodes. In regular, one-layered social networks, two nodes - i.e. people are connected with a single edge whereas in the multi-layered social networks, there may be many links of different types for a pair of nodes. Nowadays data about people and their interactions, which exists in all social media, provides information about many different types of relationships within one network. Analysing this data one can obtain knowledge not only about the structure and characteristics of the network but also gain understanding about semantic of human relations. Are they direct or not? Do people tend to sustain single or multiple relations with a given person? What types of communication is the most important for them? Answers to these and more questions enable us to draw conclusions about semantic of human interactions. Unfortunately, most of the methods used for social network analysis (SNA) may be applied only to one-layered social networks. Thus, some new structural measures for multi-layered social networks are proposed in the paper, in particular: cross-layer clustering coefficient, cross-layer degree centrality and various versions of multi-layered degree centralities. Authors also investigated the dynamics of multi-layered neighbourhood for five different layers within the social network. The evaluation of the presented concepts on the real-world dataset is presented. The measures proposed in the paper may directly be used to various methods for collective classification, in which nodes are assigned to labels according to their structural input features.Comment: 16 pages, International Journal of Computational Intelligence System

How to Create an Innovation Accelerator

Too many policy failures are fundamentally failures of knowledge. This has become particularly apparent during the recent financial and economic crisis, which is questioning the validity of mainstream scholarly paradigms. We propose to pursue a multi-disciplinary approach and to establish new institutional settings which remove or reduce obstacles impeding efficient knowledge creation. We provided suggestions on (i) how to modernize and improve the academic publication system, and (ii) how to support scientific coordination, communication, and co-creation in large-scale multi-disciplinary projects. Both constitute important elements of what we envision to be a novel ICT infrastructure called "Innovation Accelerator" or "Knowledge Accelerator".Comment: 32 pages, Visioneer White Paper, see http://www.visioneer.ethz.c

22nd Annual Conference Program

Professional and Organizational Development Network in Higher Education: Mission Statement Welcome 1997-98 Core Committee Executive Directors/Presidents Acknowledgments Conference Overview Sessions Resort Conference Cente

Evaluating the Inclusiveness of Artificial Intelligence Software in Enhancing Project Management Efficiency -- A Review

The rise of advanced technology in project management (PM) highlights a crucial need for inclusiveness. This work examines the enhancement of both inclusivity and efficiency in PM through technological integration, focusing on defining and measuring inclusiveness. This approach illuminates how inclusivity-centered technology can significantly elevate project outcomes. The research navigates through the challenges of achieving inclusivity, mainly biases in learning databases and the design process of these technologies, assessment of transformative potential of these technologies, particularly in automating tasks like data collection and analysis, thus enabling managers to prioritize human-centric aspects of projects. However, the integration of such technology transcends efficiency, indicating a paradigm shift in understanding their societal roles. This shift necessitates a new approach in the development of these systems to prevent perpetuating social inequalities. We proposed a methodology involving criteria development for evaluating the inclusiveness and effectiveness of these technologies. This methodical approach is vital to comprehensively address the challenges and limitations inherent in these systems. Emphasizing the importance of inclusivity, the study advocates for a balance between technological advancement and ethical considerations, calling for a holistic understanding and regulation. In conclusion, the paper underscores that while these technologies can significantly improve outcomes, their mindful integration, ensuring inclusivity, is paramount. This exploration into the ethical and practical aspects of technology in PM contributes to a more informed and balanced approach within the field

Incentivizing Exploration with Selective Data Disclosure

We study the design of rating systems that incentivize (more) efficient social learning among self-interested agents. Agents arrive sequentially and are presented with a set of possible actions, each of which yields a positive reward with an unknown probability. A disclosure policy sends messages about the rewards of previously-chosen actions to arriving agents. These messages can alter agents' incentives towards exploration, taking potentially sub-optimal actions for the sake of learning more about their rewards. Prior work achieves much progress with disclosure policies that merely recommend an action to each user, but relies heavily on standard, yet very strong rationality assumptions. We study a particular class of disclosure policies that use messages, called unbiased subhistories, consisting of the actions and rewards from a subsequence of past agents. Each subsequence is chosen ahead of time, according to a predetermined partial order on the rounds. We posit a flexible model of frequentist agent response, which we argue is plausible for this class of "order-based" disclosure policies. We measure the success of a policy by its regret, i.e., the difference, over all rounds, between the expected reward of the best action and the reward induced by the policy. A disclosure policy that reveals full history in each round risks inducing herding behavior among the agents, and typically has regret linear in the time horizon $T$. Our main result is an order-based disclosure policy that obtains regret $\tilde{O}(\sqrt{T})$. This regret is known to be optimal in the worst case over reward distributions, even absent incentives. We also exhibit simpler order-based policies with higher, but still sublinear, regret. These policies can be interpreted as dividing a sublinear number of agents into constant-sized focus groups, whose histories are then revealed to future agents

Google Glass App for Displaying ASL Videos for Deaf Children – The Preliminary Race

Glass Vision 3D is a grant-funded project focused on the goal of developing and researching the feasibility & usability of a Google Glass app that will allow young Deaf children to look at an object in the classroom and see an augmented reality projection that displays an American Sign Language (ASL) related video. Session will show the system (Glass app) that was developed and summarize feedback gathered during focus-group testing of the prototype

Mobile Learning Application with Cloud Computing

This project focuses on the development of M-Learning and Performance Tracking System at university level. The system provides mobility for the University students to do revision through the exercises and perform immediate tracking and analysis on the results. The project also served as a channel for students to access the latest information and news in the industry. The core problems that I had identified before I initiate this project are the immobility and limited features of current learning system which might causing the ineffective of learning among the university student. The inconvenience of the current system also included the trouble in checking their academic performance constantly from time to time. The primary goal of this research is to investigate the acceptability of the university students of m-learning, designing m-learning features that would help students to improve their academic performance, and develop the system which is able to cater the needs and meet the expectation of the students and lecturers. The methodology adapted in this project is phased development methodology that breaks the projects into 3 stages which are development of quizzes, development of performance tracking and last stage is the library function. The process involved planning, analysis, design, and last but not least implementation. As the result at the end of the project, the result found that the project is feasible with high acceptance level from the university students who believe that mobile learning is useful in learning. However more improvement has to be made on the project especially on the performance tracking method. For future development suggestions, we can adopt several methods in knowledge management in performance tracking to provide more accurate suggestions for the students. Cross platform can be achieved by adapting the HTML5 technology into the development. Cloud computing is important for the development of smartphone program with limited memory and capacity ability

25th Annual Conference Program

Welcome, by Virleen Carlson (Conference Coordinator), Bill Burke (Program Chair), Christine Stanley (President) Core Committee, 2000-2001 POD Presidents/Conference Sites Conference Overview Acknowledgements Pre-Conference Workshops Conference Schedule Mission Statemen

Google Glass App for Displaying ASL Videos for Deaf Children – The Preliminary Race

Glass Vision 3D is a grant-funded project focused on the goal of developing and researching the feasibility & usability of a Google Glass app that will allow young Deaf children to look at an object in the classroom and see an augmented reality projection that displays an American Sign Language (ASL) related video. Session will show the system (Glass app) that was developed and summarize feedback gathered during focus-group testing of the prototype