Numerical Analysis and Scientific Computing Commons^™

Shortest Path Computation With No Information Leakage, Kyriakos Mouratidis, Man Lung Yiu

Research Collection School Of Computing and Information Systems

Shortest path computation is one of the most common queries in location-based services (LBSs). Although particularly useful, such queries raise serious privacy concerns. Exposing to a (potentially untrusted) LBS the client’s position and her destination may reveal personal information, such as social habits, health condition, shopping preferences, lifestyle choices, etc. The only existing method for privacy-preserving shortest path computation follows the obfuscation paradigm; it prevents the LBS from inferring the source and destination of the query with a probability higher than a threshold. This implies, however, that the LBS still deduces some information (albeit not exact) about the client’s location …

Modeling Concept Dynamics For Large Scale Music Search, Jialie Shen, Hwee Hwa Pang, Meng Wang, Shuicheng Yan

Research Collection School Of Computing and Information Systems

Continuing advances in data storage and communication technologies have led to an explosive growth in digital music collections. To cope with their increasing scale, we need effective Music Information Retrieval (MIR) capabilities like tagging, concept search and clustering. Integral to MIR is a framework for modelling music documents and generating discriminative signatures for them. In this paper, we introduce a multimodal, layered learning framework called DMCM. Distinguished from the existing approaches that encode music as an ensemble of order-less feature vectors, our framework extracts from each music document a variety of acoustic features, and translates them into low-level encodings over …

Topic Discovery From Tweet Replies, Bingtian Dai, Ee Peng Lim, Philips Kokoh Prasetyo

Research Collection School Of Computing and Information Systems

Twitter is a popular online social information network service which allows people to read and post messages up to 140 characters, known as “tweets”. In this paper, we focus on the tweets between pairs of individuals, i.e., the tweet replies, and propose a generative model to discover topics among groups of twitter users. Our model has then been evaluated with a tweet dataset to show its effectiveness.

Joint Learning For Coreference Resolution With Markov Logic, Yang Song, Jing Jiang, Xin Zhao, Sujian Li, Houfeng Wang

Research Collection School Of Computing and Information Systems

Pairwise coreference resolution models must merge pairwise coreference decisions to generate final outputs. Traditional merging methods adopt different strategies such as the best first method and enforcing the transitivity constraint, but most of these methods are used independently of the pairwise learning methods as an isolated inference procedure at the end. We propose a joint learning model which combines pairwise classification and mention clustering with Markov logic. Experimental results show that our joint learning system outperforms independent learning systems. Our system gives a better performance than all the learning-based systems from the CoNLL-2011 shared task on the same dataset. Compared …

Identifying Event-Related Bursts Via Social Media Activities, Xin Zhao, Baihan Shu, Jing Jiang, Yang Song, Hongfei Yan, Xiaoming Li

Research Collection School Of Computing and Information Systems

Activities on social media increase at a dramatic rate. When an external event happens, there is a surge in the degree of activities related to the event. These activities may be temporally correlated with one another, but they may also capture different aspects of an event and therefore exhibit different bursty patterns. In this paper, we propose to identify event-related bursts via social media activities. We study how to correlate multiple types of activities to derive a global bursty pattern. To model smoothness of one state sequence, we propose a novel function which can capture the state context. The experiments …

Enhancing Access Privacy Of Range Retrievals Over B+Trees, Hwee Hwa Pang, Jilian Zhang, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

Users of databases that are hosted on shared servers cannot take for granted that their queries will not be disclosed to unauthorized parties. Even if the database is encrypted, an adversary who is monitoring the I/O activity on the server may still be able to infer some information about a user query. For the particular case of a B+-tree that has its nodes encrypted, we identify properties that enable the ordering among the leaf nodes to be deduced. These properties allow us to construct adversarial algorithms to recover the B+-tree structure from the I/O traces generated by range queries. Combining …

Finding Bursty Topics From Microblogs, Qiming Diao, Jing Jiang, Feida Zhu, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Microblogs such as Twitter reflect the general public’s reactions to major events. Bursty topics from microblogs reveal what events have attracted the most online attention. Although bursty event detection from text streams has been studied before, previous work may not be suitable for microblogs because compared with other text streams such as news articles and scientific publications, microblog posts are particularly diverse and noisy. To find topics that have bursty patterns on microblogs, we propose a topic model that simultaneousy captures two observations: (1) posts published around the same time are more likely to have the same topic, and (2) …

Logistics Orchestration Modeling And Evaluation For Humanitarian Relief, Hoong Chuin Lau, Zhengping Li, Xin Du, Heng Jiang, Robert De Souza

Research Collection School Of Computing and Information Systems

This paper proposes an orchestration model for post-disaster response that is aimed at automating the coordination of scarce resources that minimizes the loss of human lives. In our setting, different teams are treated as agents and their activities are "orchestrated" to optimize rescue performance. Results from simulation are analysed to evaluate the performance of the optimization model.

The R Journal (June 2012) 4(1): Complete Issue, The R Foundation

The R Journal

Contributed Research Articles

Analysing Seasonal Data, Adrian G. Barnett, Peter Baker, and Annette J. Dobson

MARSS: Multivariate Autoregressive State-space Models for Analyzing Time-series Data, Elizabeth E. Holmes, Eric J. Ward, and Kellie Wills

openair: Data Analysis Tools for the Air Quality Community, Karl Ropkins and David C. Carslaw

Foreign Library Interface, Daniel Adler

Vdgraph: A Package for Creating Variance Dispersion Graphs, John Lawson

xgrid and R: Parallel Distributed Processing Using Heterogeneous Groups of Apple Computers, Sarah C. Anoke, Yuting Zhao, Rafael Jaeger, and Nicholas J. Horton

maxent: An R Package for Low-memory Multinomial Logistic Regression with Support for Semi-automated Text …

Who Did What? The Roles Of R Package Authors And How To Refer To Them, Kurt Hornik, Duncan Murdoch, Achim Zeileis

The R Journal

Computational infrastructure for rep resenting persons and citations has been avail able in R for several years, but has been restructured through enhanced classes "person" and "bibentry" in recent versions of R. The new features include support for the specification of the roles of package authors (e.g. maintainer, author, contributor, translator, etc.) and more flexible formatting/printing tools among various other improvements. Here, we introduce the new classes and their methods and indicate how this functionality is employed in the management of R packages. Specifically, we show how the authors of R packages can be specified along with their roles in …

Xgrid And R: Parallel Distributed Processing Using Heterogeneous Groups Of Apple Computers, Sarah C. Anoke, Yuting Zhao, Rafael Jaeger, Nicholas J. Horton

The R Journal

The Apple Xgrid system provides access to groups (or grids) of computers that can be used to facilitate parallel processing. We describe the xgrid package which facilitates access to this system to undertake independent simulations or other long-running jobs that can be divided into replicate runs within R. Detailed examples are provided to demonstrate the interface, along with results from a simulation study of the performance gains using a variety of grids. Use of the grid for “embarassingly parallel” independent jobs has the potential for major speedups in time to completion. Appendices provide guidance on setting up the workflow, utilizing …

Openair: Data Analysis Tools For The Air Quality Community, Karl Ropkins, David C. Carslaw

The R Journal

The openair package contains data analysis tools for the air quality community. This paper provides an overview of data importers, main functions, and selected utilities and workhorse functions within the package and the function output class, as of package version 0.4-14. It is intended as an explanation of the rationale for the package and a technical description for those wishing to work more inter actively with the main functions or develop additional functions to support ‘higher level’ use of openair and R.

Maxent: An R Package For Low-Memory Multinomial Logistic Regression With Support For Semi-Automated Text Classification, Timothy P. Jurka

The R Journal

maxent is a package with tools for data classification using multinomial logistic regression, also known as maximum entropy. The focus of this maximum entropy classifier is to minimize memory consumption on very large datasets, particularly sparse document-term matrices represented by the tm text mining pack age.

Marss: Multivariate Autoregressive State-Space Models For Analyzing Time-Series Data, Elizabeth E. Holmes, Eric J. Ward, Kellie Wills

The R Journal

MARSS is a package for fitting multivariate autoregressive state-space models to time-series data. The MARSS package implements state-space models in a maximum likelihood framework. The core functionality of MARSSis based on likelihood maximization using the Kalman filter/smoother, combined with an EM algorithm. To make comparisons with other packages available, parameter estimation is also permitted via direct search routines avail able in ’optim’. The MARSS package allows data to contain missing values and allows a wide variety of model structures and constraints to be specified (such as fixed or shared parameters). In addition to model-fitting, the package provides bootstrap routines for …

Vdgraph: A Package For Creating Variance Dispersion Graphs, John Lawson

The R Journal

This article introduces the package Vdgraph that is used form a king variance dispersion graphs of response surface designs.The package includes functions that make the variance dispersion graph of one design or compare variance dispersion graphs of two designs, which are stored in data frames or matrices.The package also contains several minimum run response surface designs (stored as matrices) that are not available in other R packages.

Analysing Seasonal Data, Adrian G. Barnett, Peter Baker, Annette J. Dobson

The R Journal

Many common diseases, such as the flu and cardiovascular disease, increase markedly in winter and dip in summer. These seasonal patterns have been part of life for millennia and were first noted in ancient Greece by both Hippocrates and Herodotus. Recent interest has focused on climate change, and the concern that seasons will become more extreme with harsher winter and summer weather. We describe a set of R functions designed to model seasonal pat terns in disease. We illustrate some simple descriptive and graphical methods, a more complex method that is able to model non-stationary patterns, and the case-crossover to …

Foreign Library Interface, Daniel Adler

The R Journal

We present an improved Foreign Function Interface (FFI) for R to call arbitary native functions without the need for C wrapper code. Further we discuss a dynamic linkage framework for binding standard C libraries to R across platforms using a universal type information format. The package rdyncall comprises the framework and an initial repository of cross platform bindings for standard libraries such as (legacy and modern) OpenGL, the family of SDL libraries and Expat. The package enables system level programming using the R language; sample applications are given in the article. We out line the underlying automation tool-chain that extracts …

Sumo: An Authenticating Web Application With An Embedded R Session, Timothy T. Bergsma, Michael S. Smith

The R Journal

Sumo is a web application intended as a template for developers. It is distributed as a Java ‘war’ file that deploys automatically when placed in a Servlet container’s ‘webapps’ directory. If a user supplies proper credentials, Sumocreates a session-specific Secure Shell connection to the host and a user-specific R session over that connection. Developers may write dynamic server pages that make use of the persistent R session and user-specific file space. The supplied example plots a data set conditional on preferences indicated by the user; it also displays some static text. A companion server page al lows the user to …

Modeling Diffusion In Social Networks Using Network Properties, Duc Minh Luu, Ee Peng Lim, Tuan Anh Hoang, Chong Tat Freddy Chua

Research Collection School Of Computing and Information Systems

"Diffusion of items occurs in social networks due to spreading of items through word of mouth and exogenous factors. These items may be news, products, videos, advertisements or contagious viruses. When a user purchases or consumes one of such items, we say that she adopts the item and she becomes an item adopter. Previous research has studied diffusion process at both the macro and micro levels. The former models the number of item adopters in the diffusion process while the latter determines which individuals adopt item. Both macro and micro level models have their merits and limitations. In this paper, …

Virality And Susceptibility In Information Diffusions, Tuan-Anh Hoang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Viral diffusion allows a piece of information to widely and quickly spread within the network of users through word-ofmouth. In this paper, we study the problem of modeling both item and user factors that contribute to viral diffusion in Twitter network. We identify three behaviorial factors, namely user virality, user susceptibility and item virality, that contribute to viral diffusion. Instead of modeling these factors independently as done in previous research, we propose a model that measures all the factors simultaneously considering their mutual dependencies. The model has been evaluated on both synthetic and real datasets. The experiments show that our …

Visualizing Media Bias Through Twitter, Jisun An, Meeyoung Cha, Gummadi, Krishna, Jon Crowcroft, Daniele Queria

Research Collection School Of Computing and Information Systems

Traditional media outlets are known to report political news in a biased way, potentially affecting the political beliefs of the audience and even altering their voting behaviors. Therefore, tracking bias in everyday news and building a platform where people can receive balanced news information is important. We propose a model that maps the news media sources along a dimensional dichotomous political spectrum using the co-subscriptions relationships inferred by Twitter links. By analyzing 7 million follow links, we show that the political dichotomy naturally arises on Twitter when we only consider direct media subscription. Furthermore, we demonstrate a real-time Twitter-based application …

Software For Estimation Of Human Transcriptome Isoform Expression Using Rna-Seq Data, Kristen Johnson

LSU New Orleans Theses and Dissertations

The goal of this thesis research was to develop software to be used with RNA-Seq data for transcriptome quantification that was capable of handling multireads and quantifying isoforms on a more global level. Current software available for these purposes uses various forms of parameter alteration in order to work with multireads. Many still analyze isoforms per gene or per researcher determined clusters as well. By doing so, the effects of multireads are diminished or possibly wrongly represented. To address this issue, two programs, GWIE and ChromIE, were developed based on a simple iterative EM-like algorithm with no parameter manipulation. These …

A Normal Truncated Skewed-Laplace Model In Stochastic Frontier Analysis, Junyi Wang

Masters Theses & Specialist Projects

Stochastic frontier analysis is an exciting method of economic production modeling that is relevant to hospitals, stock markets, manufacturing factories, and services. In this paper, we create a new model using the normal distribution and truncated skew-Laplace distribution, namely the normal-truncated skew-Laplace model. This is a generalized model of the normal-exponential case. Furthermore, we compute the true technical efficiency and estimated technical efficiency of the normal-truncated skewed-Laplace model. Also, we compare the technical efficiencies of normal-truncated skewed-Laplace model and normal-exponential model.

Organizing User Search Histories, Heasoo Hwang, Hady W. Lauw, Lise Getoor, Alexandros Ntoulas

Research Collection School Of Computing and Information Systems

Users are increasingly pursuing complex task-oriented goals on the web, such as making travel arrangements, managing finances, or planning purchases. To this end, they usually break down the tasks into a few codependent steps and issue multiple queries around these steps repeatedly over long periods of time. To better support users in their long-term information quests on the web, search engines keep track of their queries and clicks while searching online. In this paper, we study the problem of organizing a user's historical queries into groups in a dynamic and automated fashion. Automatically identifying query groups is helpful for a …

Comparative Study Of Various Data Collection Software Used For Seat-Belt Observation Surveys, Atul Sancheti, Puneet Lakhanpal, Sergio Contreras, Pushkin Kachroo, Masha Wilson

College of Engineering: Graduate Celebration Programs

Every year, Click It or Ticket (CIOT) mobilization is held in U.S. which aims at increasing seat-belt usage awareness among the people. Data collection for assessing current seat-belt usage rates and campaign design for influencing mass audience are the two most important components of the mobilization. This paper presents a comparative study of various data collections software used for seat-belt observational surveys. The comparison is based on the speed and accuracy of the data collected from different software at the same locations and at the same time of the day.

User Behaviour In The Webpac: Insights From Google Analytics, Yiu On Li, Christopher Chan

Hong Kong Innovative Users Group Meetings

No abstract provided.

Random Number Generation: Types And Techniques, David F. Dicarlo

Senior Honors Theses

What does it mean to have random numbers? Without understanding where a group of numbers came from, it is impossible to know if they were randomly generated. However, common sense claims that if the process to generate these numbers is truly understood, then the numbers could not be random. Methods that are able to let their internal workings be known without sacrificing random results are what this paper sets out to describe. Beginning with a study of what it really means for something to be random, this paper dives into the topic of random number generators and summarizes the key …

Obfuscating The Topical Intention In Enterprise Text Search, Hwee Hwa Pang, Xiaokui Xiao, Jialie Shen

Research Collection School Of Computing and Information Systems

The text search queries in an enterprise can reveal the users' topic of interest, and in turn confidential staff or business information. To safeguard the enterprise from consequences arising from a disclosure of the query traces, it is desirable to obfuscate the true user intention from the search engine, without requiring it to be re-engineered. In this paper, we advocate a unique approach to profile the topics that are relevant to the user intention. Based on this approach, we introduce an (ε ₁, ε ₂)-privacy model that allows a user to stipulate that topics relevant to her intention …

Mining Social Dependencies In Dynamic Interaction Networks, Freddy Chong-Tat Chua, Hady W. Lauw, Ee Peng Lim

Research Collection School Of Computing and Information Systems

User-to-user interactions have become ubiquitous in Web 2.0. Users exchange emails, post on newsgroups, tag web pages, co-author papers, etc. Through these interactions, users co-produce or co-adopt content items (e.g., words in emails, tags in social bookmarking sites). We model such dynamic interactions as a user interaction network, which relates users, interactions, and content items over time. After some interactions, a user may produce content that is more similar to those produced by other users previously. We term this effect social dependency, and we seek to mine from such networks the degree to which a user may be socially dependent …

Preconditioning Visco-Resistive Mhd For Tokamak Plasmas, Daniel R. Reynolds, Ravi Samtaney, Hilari C. Tiedeman

Mathematics Research

No abstract provided.