Numerical Analysis and Scientific Computing Commons^™

Image Collection Summarization Via Dictionary Learning For Sparse Representation, Chunlei Yang, Jialie Shen, Jinye Peng, Jianping Fan

Research Collection School Of Computing and Information Systems

In this paper, a novel approach is developed to achieve automatic image collection summarization. The effectiveness of the summary is reflected by its ability to reconstruct the original set or each individual image in the set. We have leveraged the dictionary learning for sparse representation model to construct the summary and to represent the image. Specifically we reformulate the summarization problem into a dictionary learning problem by selecting bases which can be sparsely combined to represent the original image and achieve a minimum global reconstruction error, such as MSE (Mean Square Error). The resulting “Sparse Least Square” problem is NP-hard, …

Online Multi-Modal Distance Learning For Scalable Multimedia Retrieval, Hao Xia, Pengcheng Wu, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

In many real-word scenarios, e.g., multimedia applications, data often originates from multiple heterogeneous sources or are represented by diverse types of representation, which is often referred to as "multi-modal data". The definition of distance between any two objects/items on multi-modal data is a key challenge encountered by many real-world applications, including multimedia retrieval. In this paper, we present a novel online learning framework for learning distance functions on multi-modal data through the combination of multiple kernels. In order to attack large-scale multimedia applications, we propose Online Multi-modal Distance Learning (OMDL) algorithms, which are significantly more efficient and scalable than the …

Structures Of Broken Ties: Exploring Unfollow Behavior On Twitter, Bo Xu, Yun Huang, Haewoon Kwak

Research Collection School Of Computing and Information Systems

This study investigates unfollow behavior in Twitter, i.e. people removing others from their Twitter following lists. Considering the interdependency and dynamics of unfollow decisions, we use actor-oriented modeling (SIENA) to examine the impacts of reciprocity, status, embeddedness, homophily, and informativeness on tie dissolution. Focusing on ordinary users in tightly-knitted user groups, the results show that relational properties play key roles in the emergence of unfollow behavior: mutual following relations and common followees reduce the likelihood of unfollowing. And unfollow tends to be reciprocal: when a user is unfollowed by someone, he or she will unfollow back. However, there is no …

Using Mapreduce Streaming For Distributed Life Simulation On The Cloud, Atanas Radenski

Mathematics, Physics, and Computer Science Faculty Books and Book Chapters

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable …

Utility Of Potential Misdiagnoses In Predicting Foodborne Outbreaks, Lucia Lucia, Artur Dubrawski, Lujie Chen

Research Collection School Of Computing and Information Systems

To investigate utility of using inpatient and emergency room diagnoses to detect outbreaks of Salmonellosis in humans. To quantify the impact of including in the analysis cases diagnosed with conditions that may have physiological appearance similar to Salmonellosis.

On Identifying And Analyzing Significant Nodes In Protein-­Protein Interaction Networks, Rohan Khazanchi, Kathryn Dempsey Cooper, Ishwor Thapa, Hesham Ali

Interdisciplinary Informatics Faculty Proceedings & Presentations

Network theory has been used for modeling biological data as well as social networks, transportation logistics, business transcripts, and many other types of data sets. Identifying important features/parts of these networks for a multitude of applications is becoming increasingly significant as the need for big data analysis techniques grows. When analyzing a network of protein-protein interactions (PPIs), identifying nodes of significant importance can direct the user toward biologically relevant network features. In this work, we propose that a node of structural importance in a network model can correspond to a biologically vital or significant property. This relationship between topological and …

On Mining Biological Signals Using Correlation Networks, Kathryn Dempsey Cooper, Ishwor Thapa, Claudia Cortes, Zack Eriksen, Dhundy Raj Bastola, Hesham Ali

Interdisciplinary Informatics Faculty Proceedings & Presentations

Correlation networks have been used in biological networks to analyze and model high-throughput biological data, such as gene expression from microarray or RNA-seq assays. Typically in biological network modeling, structures can be mined from these networks that represent biological functions; for example, a cluster of proteins in an interactome can represent a protein complex. In correlation networks built from high-throughput gene expression data, it has often been speculated or even assumed that clusters represent sets of genes that are coregulated. This research aims to validate this concept using network systems biology and data mining by identification of correlation network clusters …

A Parallel Template For Implementing Filters For Biological Correlation Networks, Kathryn Dempsey Cooper, Vladimir Ufimtsev, Sanjukta Bhowmick, Hesham Ali

Interdisciplinary Informatics Faculty Publications

High throughput biological experiments are critical for their role in systems biology – the ability to survey the state of cellular mechanisms on the broad scale opens possibilities for the scientific researcher to understand how multiple components come together, and what goes wrong in disease states. However, the data returned from these experiments is massive and heterogeneous, and requires intuitive and clever computational algorithms for analysis. The correlation network model has been proposed as a tool for modeling and analysis of this high throughput data; structures within the model identified by graph theory have been found to represent key players …

Multimedia Recommendation: Technology And Techniques, Jialie Shen, Meng Wang, Shuicheng Yan, Peng Cui

Research Collection School Of Computing and Information Systems

In recent years, we have witnessed a rapid growth in the availability of digital multimedia on various application platforms and domains. Consequently, the problem of information overload has become more and more serious. In order to tackle the challenge, various multimedia recommendation technologies have been developed by different research communities (e.g., multimedia systems, information retrieval, machine learning and computer version). Meanwhile, many commercial web systems (e.g., Flick, YouTube, and Last.fm) have successfully applied recommendation techniques to provide users personalized content and services in a convenient and flexible way. When looking back, the information retrieval (IR) community has a long history …

Hypergraph Index: An Index For Context-Aware Nearest Neighbor Query On Social Networks, Yazhe Wang, Baihua Zheng

Research Collection School Of Computing and Information Systems

Social network has been touted as the No. 2 innovation in a recent IEEE Spectrum Special Report on “Top 11 Technologies of the Decade”, and it has cemented its status as a bona fide Internet phenomenon. With more and more people starting using social networks to share ideas, activities, events, and interests with other members within the network, social networks contain a huge amount of content. However, it might not be easy to navigate social networks to find specific information. In this paper, we define a new type of queries, namely context-aware nearest neighbor (CANN) search over social network to …

Towards Next-Generation Multimedia Recommendation Systems, Jialie Shen, Shuicheng Yan, Xian-Sheng Hua

Research Collection School Of Computing and Information Systems

Empowered by advances in information technology, such as social media network, digital library and mobile computing, there emerges an ever-increasing amounts of multimedia data. As the key technology to address the problem of information overload, multimedia recommendation system has been received a lot of attentions from both industry and academia. This course aims to 1) provide a series of detailed review of state-of-the-art in multimedia recommendation; 2) analyze key technical challenges in developing and evaluating next generation multimedia recommendation systems from different perspectives and 3) give some predictions about the road lies ahead of us.

Business Intelligence And Analytics: Research Directions, Ee Peng Lim, Hsinchun Chen, Guoqing Chen

Research Collection School Of Computing and Information Systems

Business intelligence and analytics (BIA) is about the development of technologies, systems, practices, and applications to analyze critical business data so as to gain new insights about business and markets. The new insights can be used for improving products and services, achieving better operational efficiency, and fostering customer relationships. In this article, we will categorize BIA research activities into three broad research directions: (a) big data analytics, (b) text analytics, and (c) network analytics. The article aims to review the state-of-the-art techniques and models and to summarize their use in BIA applications. For each research direction, we will also determine …

Cqarank: Jointly Model Topics And Expertise In Community Question Answering, Liu Yang, Minghui Qiu, Swapna Gottopati, Feida Zhu, Jing Jiang, Huiping Sun, Zhong Chen

Research Collection School Of Computing and Information Systems

Community Question Answering (CQA) websites, where people share expertise on open platforms, have become large repositories of valuable knowledge. To bring the best value out of these knowledge repositories, it is critically important for CQA services to know how to find the right experts, retrieve archived similar questions and recommend best answers to new questions. To tackle this cluster of closely related problems in a principled approach, we proposed Topic Expertise Model (TEM), a novel probabilistic generative model with GMM hybrid, to jointly model topics and expertise by integrating textual content model and link structure analysis. Based on TEM results, …

The Impact Of Smartphone Adoption On Consumers’ Switching Behavior In Broadband And Cable Tv Services, Gwangjae Jung

Research Collection School Of Computing and Information Systems

The emergence of smartphones has brought a technology disruption to the telecom business. Due to the various services offered in association with smartphones, people can surf the web or watch TV. This research is related to telecom services overall, and has the goal of finding the impact of smartphone adoption to consumers’ switching behavior in broadband and cable TV services. This research adopts a quasi-experimental design and investigates the causal effect of smartphone service adoption on broadband and cable TV service choices. The data collection involves five years of consumer service subscriptions in a Singaporean telecommunications company. I tested for …

The R Journal (December 2012) 4(2): Complete Issue, The R Foundation

The R Journal

Contributing Articles

What's in a Name? Paul Murrell

It's Not What You Draw, It's What You Don't Draw, Paul Murrell

Debugging grid Graphics, Paul Murrell and Velvet Ly

frailtyHL: A Package for Fitting Frailty Models with H-likelihood, Il Do Ha, Maengseok Noh, and Youngjo Lee

influence.ME: Tools for Detecting Influential Data in Mixed Effects Models, Rense Nieuwenhuis, Manfred te Grotenhuis and Ben Pelzer

The crs Package: Nonparametric Regression Splines for Continuous and Categorical Predictors, Zhenghua Nie and Jeffrey S. Racine

Rfit: Rank-based Estimation for Linear Models, John D. Kloke and Joseph W. McKean

Graphical Markov Models with Mixed Graphs in …

The Crs Package: Nonparametric Regression Splines For Continuous And Categorical Predictors, Zhenghua Nie, Jeffery S. Racine

The R Journal

A new package crs is introduced for computing nonparametric regression (and quantile) splines in the presence of both continuous and categorical predictors. B-splines are employed in the regression model for the continuous predictors and kernel weighting is employed for the categorical predictors. We also de velop a simple R interface to NOMAD, which is a mixed integer optimization solver used to compute optimal regression spline solutions.

Influence.Me: Tools For Detecting Influential Data In Mixed Effects Models, Rense Nieuwenhuis, Manfred Te Grotenhuis, Ben Pelzer

The R Journal

influence.ME provides tools for detecting influential data in mixed effects models. The application of these models has become common practice, but the development of diagnostic tools has lagged behind. influence.ME calculates standardized measures of influential data for the point estimates of generalized mixed effects models, such as DFBETAS, Cook’s distance, as well as percentile change and a test for changing levels of significance. influence.ME calculates these measures of influence while ac counting for the nesting structure of the data. The package and measures of influential data are introduced, a practical example is given, and strategies for dealing with influential data …

Graphical Markov Models With Mixed Graphs In R, Kayvan Sadeghi, Giovanni M. Marchetti

The R Journal

In this paper we provide a short tuto rial illustrating the new functions in the package ggm that deal with ancestral, summary and ribbonless graphs. These are mixed graphs (containing three types of edges) that are important because they capture the modified independence structure after marginalisation over, and conditioning on, nodes of directed acyclic graphs. We provide functions to verify whether a mixed graph implies that A is independent of B given C for any disjoint sets of nodes and to generate maximal graphs inducing the same independence structure of non-maximal graphs. Finally, we provide functions to decide on the …

What's In A Name?, Paul Murrell

The R Journal

Any shape that is drawn using the grid graphics package can have a name associated with it. If a name is provided, it is possible to access, query, and modify the shape after it has been drawn. These facilities allow for very detailed customisations of plots and also for very general transformations of plots that are drawn by packages based on grid.

Frailtyhl: A Package For Fitting Frailty Models With H-Likelihood, Il Do Ha, Maengseok Noh, Youngjo Lee

The R Journal

We present the frailtyHL package for fitting semi-parametric frailty models using h likelihood. This package allows lognormal or gamma frailties for random-effect distribution, and it fits shared or multilevel frailty models for correlated survival data. Functions are provided to format and summarize the frailtyHL results. The estimates of fixed effects and frailty parameters and their standard errors are calculated. We illustrate the use of our package with three well known data sets and compare our results with various alternative R-procedures.