ppxscal/embedding_network huggingface dataset:
Investigating social network patterns within an empathic online community for older people
Authors: Ulrike Pfeil, Panayiotis Zaphiris
Venue: Computers in Human Behavior (2009)

In this paper, we study the social network structure of an online discussion board within SeniorNet, an empathic online community for older people. We apply Social Network Analysis (SNA) to analyse the communication patterns and relationships between members of the discussion board. In addition to looking at the structure of the exchanged messages within the discussion board as a whole, we also investigate associations between the communication content and the social network patterns. Our findings show distinct differences between the social network patterns of empathic and non-empathic communications. For example, members are more connected and closer to each other in the social networks that are based on empathic communication compared to non-empathic communication. Additionally our results show that the type of empathic communication (e.g. different kinds of support) is linked to the social network structure within the discussion board.
Semi-supervised Learning Based on Label Propagation through Submanifold
Authors: Jiani Hu, Weihong Deng, Jun Guo
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

A semi-supervised learning algorithm is proposed based on label propagation through submanifold. The algorithm assumes that samples lying in a local neighborhood share the same labels and the global labels changing among submanifolds is sufficiently smooth. The algorithm firstly introduces a k-nearest neighbor graph to describe local neighborhood among the data set. And then, a cost function and a constraint equation are proposed, which stand for the global smoothness of the class labels' changing and the labeled samples' information respectively. The final semi-supervised learning task is converted to a typical quadratic program, whose optimal solution can minimize the cost function and satisfy the supervised constraint. Experimental results of the algorithm on toy data, digit recognition, and text classification demonstrate the feasibility and efficiency of the proposed algorithm.
A context-aware approach based on self-organizing maps to study web-users' tendencies from their behaviour
Authors: Luca Longo, Stephen Barrett
Venue: Proceedings of the 1st International Workshop on Context-Aware Middleware and Services: affiliated with the 4th International Conference on Communication System Software and Middleware (COMSWARE 2009) (2009)

In the context of a highly volatile web of uneven quality, the identification of content deemed valuable by end users is of paramount importance. Where page content undergoes rapid change, this issue is particularly challenging. Web browsing activity represents a unique source of context by which the value of web pages can be determined via an assessment of individual user interactions, such as scrolling, clicking, saving and so forth. Over time, this data set forms a pattern of activity which can be mined for meaning. In this paper we present an approach to web content, based on Kohonen mapping, used to generate a topological model of users' behaviour over web-pages. Each web-document can thus be represented as a semantic map built by adopting unsupervised techniques where similar users' behaviour are mapped close together, with identification of information stability emerging as a by product of the identification of similarity in user activity over content. In this model, the more similar the outputs of the map for each user who has endorsed a web-page, the more the web site is considered current or in context with changing information. We illustrate the potential application of this approach to our ongoing work in social search.
Voyagers and voyeurs: supporting social data analysis
Authors: Jeffrey Heer
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

In recent years, researchers and entrepreneurs have introduced new online services for data collection and analysis, often relying on interactive visualizations to enable mass interaction with data. These sites represent the first step in what looks to be a growing online phenomenon: social data analysis, that is, collective analysis of data supported by social interaction. Engaging crowds of both experts and non-experts in the process of data exploration has applications ranging from political transparency to business intelligence to citizen science. Achieving this vision, however, will require further innovation in the design of systems for collaborative data management. In this talk, I will highlight recent efforts to use the web as a platform for collectively creating, managing, and analyzing data. I will share how web citizens are collaborating with data, and discuss how we might design systems to catalyze social forms of data management and exploration.
Multi-level association rules for MP3P marketing strategies based on extensive marketing survey data
Authors: Doo Min Kyun, So Young Sohn, Jong Seok Kim
Venue: Expert Systems with Applications: An International Journal (2009)

This study analyzes the purchase patterns of MPEG Audio Layer-3 Players (MP3) customers in Korea. Factor analysis, clustering, and association rules are used to find the purchase patterns of segmented groups. From our analysis, 7 major factors were identified: technique, business, stylishness, rationale, late adaptor, pragmatic propensity, and music. Based on these factors and demographic data, six types of user groups are identified. Subsequently, we identify the chain of purchase processes of each cluster of customers. Finally, we propose target marketing strategies for segmented groups. We expect that our study results can provide direction for marketing and public relations strategies for MP3P manufacturers.
An Educator's Guide to Google Apps for Education
Authors: Chris Carey, John Lien, Maurice Draggon, Sheila Ryan
Venue:  (2007)

An Educator's Guide to Google Apps for Education outlines the numerous tools that are available for free from Google. Applications include Google Maps, Picassa, Blogger, Google Earth, Docs and Spreadsheets and many more. These applications and services can all be downloaded or used online for free! This must have teacher resource book will also help you maximize your Google searches, making time in the computer lab more productive. The handy activity guide in the back of the book helps students become more familiar with each of the applications discussed. These activities are easy to follow and fun to use. Each lesson can be tailored to fit the needs of the student. Educational suggestions in each chapter help integrate each Google Application into the classroom. An Educator's Guide to Google Apps for Education will help you utilize the Internet to its full potential. Use Google Apps to energize your classroom, to engage your students and to get your students active and using Google to the best of their ability.
Simultaneous speculative threading: a novel pipeline architecture implemented in sun's rock processor
Authors: Shailender Chaudhry, Robert Cypher, Magnus Ekman, Martin Karlsson, Anders Landin, Sherman Yip, Håkan Zeffer, Marc Tremblay
Venue: ACM SIGARCH Computer Architecture News (2009)

This paper presents Simultaneous Speculative Threading (SST), which is a technique for creating high-performance area- and power-efficient cores for chip multiprocessors. SST hardware dynamically extracts two threads of execution from a single sequential program (one consisting of a load miss and its dependents, and the other consisting of the instructions that are independent of the load miss) and executes them in parallel. SST uses an efficient checkpointing mechanism to eliminate the need for complex and power-inefficient structures such as register renaming logic, reorder buffers, memory disambiguation buffers, and large issue windows. Simulations of certain SST implementations show 18% better per-thread performance on commercial benchmarks than larger and higher-powered out-of-order cores. Sun Microsystems' ROCK processor, which is the first processor to use SST cores, has been implemented and is scheduled to be commercially available in 2009.
Probabilistic Association Rules for Item-Based Recommender Systems
Authors: Sylvain Castagnos, Armelle Brun, Anne Boyer
Venue: Proceeding of the 2008 conference on STAIRS 2008: Proceedings of the Fourth Starting AI Researchers' Symposium (2008)

Since the beginning of the 1990's, the Internet has constantly grown, proposing more and more services and sources of information. The challenge is no longer to provide users with data, but to improve the human/computer interactions in information systems by suggesting fair items at the right time. Modeling personal preferences enables recommender systems to identify relevant subsets of items. These systems often rely on filtering techniques based on symbolic or numerical approaches in a stochastic context. In this paper, we focus on item-based collaborative filtering (CF) techniques. We show that it may be difficult to guarantee a good accuracy for the high values of prediction when ratings are not enough shared out on the rating scale. Thus, we propose a new approach combining a classic CF algorithm with an item association model to get better predictions. We deal with this issue by exploiting probalistic skewnesses in triplets of items. We validate our model by using the MovieLens dataset and get a significant improvement as regards the High MAE measure.
On Finding the Social Structure among Learners in Group Learning Environments
Authors: Isaac Pak-Wah Fung
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

This paper describes a network-based approach to study the exchange of messages between students in an online group learning environment. The approach models the learners and instructor as a collection of nodes which link together with message exchange mechanisms. The mechanisms are represented as directed arcs in which their directions indicate the orientation of the flow. Regular patterns of message exchange reveal the participants as social network which structures the flow of learning information between students and instructor. The method provides quantitative information for assessing interactions.
An Apriori Based Approach to Improve On-line Advertising Performance
Authors: Giovanni Giuffrida, Vincenzo Cantone, Giuseppe Tribulato
Venue: Proceeding of the 2008 conference on Applications of Data Mining in E-Business and Finance (2008)

On-line advertising is booming. Compared to traditional media, such as Press and TV, Web advertising is cheap and offers interesting returns. Thus, it is attracting more and more consideration by the industry. In particular, it is now a consistent part of the marketing mix, that is, the set of different approaches to advertise a product. Data mining based optimization on Web advertising can take place at many different levels. From a data miner perspective, Internet advertising is a very interesting domain as it offers a very large amount of data produced at fast pace with a rich and precise amount of details. It also offers the valuable possibility of live hypothesis testing. Here we discuss an Apriori based optimization experiment we performed on live data. We show how effective such optimization is.
Routing and Aggregation Strategies for Contour Map Applications in Sensor Networks
Authors: Shoudong Zou, Ioanis Nikolaidis, Janelle Harms
Venue: Proceedings of the 7th International Conference on Wired/Wireless Internet Communications (2009)

We consider the limitations inherent in data aggregation techniques for wireless sensor networks. In particular, we illustrate the limitations of schemes in which data from a sensor are routed to the node that can perform the most effective data aggregation. We then seek alternative forms of aggregation where, in principle, it is possible to aggregate readings from many sensors into a single one. To this end, we select contour maps as the most convenient example of data representation because they are used by various applications and, at the same time, allow for aggressive data aggregation. We describe particular aggregation and routing strategies that exploit the structure of contour maps. Namely, we use clustering based on the contour map values, as well as intra---cluster and inter---cluster routing and aggregation heuristics. Simulation results demonstrate the capabilities and limitations of the various varieties of aggregation/routing strategies.
A view-based statistical system for multi-view face detection and pose estimation
Authors: Ju-Chin Chen, Jenn-Jier James Lien
Venue: Image and Vision Computing (2009)

This study develops a novel statistical system for automatic multi-view face detection and pose estimation. The five-module detection system is based on significant local facial features (or subregions) rather than the entire face. The low- and high-frequency feature information of each subregion of the facial image are extracted and projected onto the eigenspace and residual independent basis space in order to create the corresponding PCA (principal component analysis) projection weight vector and ICA (independent component analysis) coefficient vector, respectively. Therefore, the proposed system has an improved tolerance toward different facial expressions, wide viewing angles, partial occlusions and lighting conditions. Furthermore, either projection weight vectors or coefficient vectors in the PCA or ICA space have divergent distributions and are therefore modeled by using the weighted Gaussian mixture model (GMM) rather than a single Gaussian model. The GMM weights and parameters of the GMM are estimated iteratively using the Expectation-Maximization (EM) algorithm. Face detection is then performed by conducting a likelihood evaluation process based on the estimated joint probability of the weight and coefficient vectors and the corresponding geometric positions of the subregions. The use of subregion position information can reduce the risk of false acceptances. Moreover, simple cascaded rejecter module is employed to exclude 85% of the non-face images in order to enhance the overall system performance. The computational overhead is further reduced by eliminating the requirement for a residual image reconstruction process in the ICA process. Finally, the performance of the proposed system is evaluated using challenging databases. The results not only demonstrate the ability of the system to automatically identify facial images with a high degree of accuracy, but also verify its ability to estimate the fine pose angles with 5^o precision and an over 90% accuracy rate.
Recent Advances in Mechatronics, 1st edition
Authors: Ryszard Jablonski, Ryszard Jablonski, Mateusz Turkowski, Roman Szewczyk
Venue:  (2007)

Mechatronics is the synergistic combination of precision engineering, electronics, photonics and IT engineering. The main research task for mechatronics is development and control of advanced hybrid systems covering all these fields and supported by interdisciplinary studies. This book presents recent state of advances in mechatronics presented on the 7th International Conference Mechatronics 2007, hosted at the Faculty of Mechatronics, Warsaw University of Technology, Poland. The chosen topics of the conference included: Nanotechnology, Automatic Control and Robotics, Biomedical Engineering, Design Manufacturing and Testing of MEMS, Metrology, Photonics, Mechatronic Products. The selected papers give an overview of the state-of-the-art and present new research results and prospects of the future development in this interdisciplinary field of mechatronic systems. This book will provide up-to-date and useful knowledge for researchers and engineers involved in mechatronics and related fields.
Towards Developing Adjustable Software: A Case Study with the Lyee Approach
Authors: Sergei Gorlatch, Tae Kameda, Issam Hamido Fujita, Michiru Tanaka, Yutaka Funyu, Osamu Arai
Venue: Proceeding of the 2006 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the fifth SoMeT_06 (2006)

Adjustable programs allow the user to introduce changes and optimizations to the program in the late phases of the software lifecycle. Maintaining and enhancing software to cope with newly discovered problems or new requirements can take far more time than the initial development of the software. In conventional programs, such changes are usually made by software engineers, which makes the process time-consuming and costly. The main contribution of this paper is the novel approach to developing adjustable software by means of interfaces that are built into a program during its specification and development. These interfaces are made open to the user who can perform later changes of the program behavior and functionality, without possessing a specific knowledge in programming languages or software engineering. We present our approach to adjustability and its implementation in the context of the Lyee programming methodology, in which programs are generated (semi)automatically from high-level specifications developed by a non-expert user. Our approach is illustrated using an application case study --a web-based shop --for which we describe the implementation of adjustability using interfaces realized by the Lyee programming method.
Categories for Description of Dynamic Production Systems
Authors: Vadim Stefanuk, Alexander Zhozhikashvili
Venue: Proceeding of the 2006 conference on Knowledge-Based Software Engineering: Proceedings of the Seventh Joint Conference on Knowledge-Based Software Engineering (2006)

Based on the categorical formalism developed for the production type knowledge-based Intelligent System, the paper describes a scheme, which allows an easy conversion of a category, build for a static production system, into a category, suitable for description of a dynamic knowledge system. The scheme is shown to be applicable for an arbitrary category. For instance, the presented examples demonstrate that the scheme might describe many different ways of introduction of dynamic properties into an intelligent system. Besides the pure dynamic intellectual systems the proposed scheme may be applied to other knowledge-based systems, where it is important and essential to store the information on the way the system inferences have been made.
Exploratory Study on the Use of Mixed Reality for Primary Science Learning
Authors: Alexis Lee-Hin Pang, Jean Yin-Chiun Phua, Wai Tuck Wu, Ratni Suriyani, Mohd Yusri Bin Mohd Noor, Ashley Pan
Venue: Proceeding of the 2007 conference on Supporting Learning Flow through Integrative Technologies (2007)

An exploratory study was conducted on the use of a Mixed Reality (MXR) prototype in a typical primary (11 years-old) class to facilitate the learning of seed germination and plant growth in the Singapore Primary Science curriculum. Quantitative analysis of pre-post test results showed no significant differences in test performance. Qualitative analysis of pupils' behaviour indicated significant engagement and motivation encouraged by the use of the technology. Issues involving pedagogical approach, MXR technology and learning are discussed. Plans for subsequent trials are also outlined.
Estimating the confidence of conditional functional dependencies
Authors: Graham Cormode, Lukasz Golab, Korn Flip, Andrew McGregor, Divesh Srivastava, Xi Zhang
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

Conditional functional dependencies (CFDs) have recently been proposed as extensions of classical functional dependencies that apply to a certain subset of the relation, as specified by a pattern tableau. Calculating the support and confidence of a CFD (i.e., the size of the applicable subset and the extent to which it satisfies the CFD)gives valuable information about data semantics and data quality. While computing the support is easier, computing the confidence exactly is expensive if the relation is large, and estimating it from a random sample of the relation is unreliable unless the sample is large. We study how to efficiently estimate the confidence of a CFD with a small number of passes (one or two) over the input using small space. Our solutions are based on a variety of sampling and sketching techniques, and apply when the pattern tableau is known in advance, and also the harder case when this is given after the data have been seen. We analyze our algorithms, and show that they can guarantee a small additive error; we also show that relative errors guarantees are not possible. We demonstrate the power of these methods empirically, with a detailed study using both real and synthetic data. These experiments show that it is possible to estimate the CFD confidence very accurately with summaries which are much smaller than the size of the data they represent.
Enhancements on proxy certification for dynamic delegation
Authors: Moutasem Shafa'Amry, Nisreen Alam Aldeen
Venue: Proceedings of the 2nd conference on European computing conference (2008)

Today, most of the e-applications and services (mainly e-banking, e-government e-commerce, e-business and grid applications) require authentication and secure access. Some of these services allow delegation. The X.509 Proxy Certificate is considered the most common technique of delegation in use today. It is proposed as a partial solution to resolve some problems of existing certification system. X.509 Proxy Certificates have been defined and standardized for the purpose of providing restricted proxying and delegation within a PKI-based authentication system. This paper deals with this delegation mechanism, as it reviews a series of conceptual, legal and implementation features, and problems for this type with it's pros and cons regarding security and privacy communication. We explore here the advantages and disadvantages of Proxy Certificate that consider the starting points for our research. We also present our suggested modification to provide improvements for delegation technologies and develop the specifications for new technology beyond current limitations. Our modification is based on the consolidation a centralized strict hierarchical and stand-alone structures through banding x.509 standard and proxy certificate together.
Towards adapting authentic learning for formal work-integrated e-learning
Authors: Christian Ostlund, Karlheinz Kautz, Lars Svensson
Venue: Proceedings of the 4th International Conference on Design Science Research in Information Systems and Technology (2009)

This poster reports from the initial steps of formulating a prescriptive design theory to support the development of scholastic/formal work-integrated e-learning systems. For this purpose a framework for authentic learning, developed and evaluated in a school setting and the eight components of design theories by Gregor and Jones has been used to guide two e-learning activities in a work setting. Adapting authentic learning to a formal work-integrated e-learning context calls for a simplification of the framework where some elements of authentic learning become peripheral whereas others become more central.
Towards Best Practices for Semantic Web Student Modelling
Authors: Mike Winter, Christopher Brooks, Jim Greer
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

Semantic Web applications offer great potential to student modellers who have traditionally struggled with issues of re-use, portability and tight coupling with learning applications. In this paper, we describe our use of ontology languages and e-learning standards to develop a loosely coupled and portable student modelling architecture used in a large-scale, distributed production learning environment. Funding for this research was provided by the LORNET grant from the National Science and Engineering Research Council of Canada.