Core Versus Peripheral Information Technology Employees And Their Impact On Firm Performance,
2013
Singapore Management University
Core Versus Peripheral Information Technology Employees And Their Impact On Firm Performance, Ling Liu, Daniel Q. Chen, Nan Hu, Indranil Bose, Garry D. Bruton
Research Collection School Of Computing and Information Systems
Scholars have widely argued, but not previously examined, that core employees with firm specific skills are critical to the firm's strategic success. This argument has led to the belief that employees whose skills are not firm specific can be readily replaced in the external market and are peripheral to the firm's strategic goals. Employing a resource based view of the firm, we find that the core information technology (IT) employees with firm specific skills are value-adding resources that aid the firm's performance whereas peripheral employees with less firm specific skills provide no value to the firm's performance. Examining the issue …
Modeling And Analysis Of Information Product Maps,
2013
University of Arkansas Little Rock
Modeling And Analysis Of Information Product Maps, Christopher Harris Heien
Theses and Dissertations
Information Product Maps are visual diagrams used to represent the inputs, processing, and outputs of data within an Information Manufacturing System. A data unit, drawn as an edge, symbolizes a grouping of raw data as it travels through this system. Processes, drawn as vertices, transform each data unit input into various forms prior to delivery to consumers. These visual representations act as documentation for all processes, and data unit transformations, leading to the final construction and delivery of an Information Product. The science of Information Quality strives to measure the fitness for use of these products, expressed by consumer satisfaction. …
Spatial Search Techniques For Mobile 3d Queries In Sensor Web Environments,
2013
Technological University Dublin
Spatial Search Techniques For Mobile 3d Queries In Sensor Web Environments, Junjun Yin, James Carswell
Articles
Developing mobile geo-information systems for sensor web applications involves technologies that can access linked geographical and semantically related Internet information. Additionally, in tomorrow’s Web 4.0 world, it is envisioned that trillions of inexpensive micro-sensors placed throughout the environment will also become available for discovery based on their unique geo-referenced IP address. Exploring these enormous volumes of disparate heterogeneous data on today’s location and orientation aware smartphones requires context-aware smart applications and services that can deal with “information overload”. 3DQ (Three Dimensional Query) is our novel mobile spatial interaction (MSI) prototype that acts as a next-generation base for human interaction within …
Session F-4: Using Web Tools And Strategies To Enhance Student Engagement,
2013
Illinois Mathematics and Science Academy
Session F-4: Using Web Tools And Strategies To Enhance Student Engagement, Jackie Naughton, Frank Tomsic
Professional Learning Day
Web tools and strategies will be introduced and modeled. Teachers will leave this session able to immediately implement the tools and strategies in their classrooms. Participants must bring their own devices.
Predicting Parkinson's Disease Progression With Smartphone Data,
2013
Wright State University - Main Campus
Predicting Parkinson's Disease Progression With Smartphone Data, Pramod Anantharam, Krishnaprasad Thirunarayan, Vahid Taslimi, Amit P. Sheth
Kno.e.sis Publications
Most of the existing approaches for detecting diseases/risk score form observations (sensor and textual) ignore the presence of any prior knowledge of the disease. In this work, we start top-down by enumerating the symptoms of Parkinson's Disease (PD) and map the symptoms to its possible manifestations in sensor observations (bottom-up). We show such manifestations and further use these manifestations as features to build classifiers to differentiate between the PD patients and the control group.
Data Visualization On Interactive Surfaces: A Research Agenda,
2013
Singapore Management University
Data Visualization On Interactive Surfaces: A Research Agenda, Petra Isenberg, Tobias Isenberg, Tobias Hesselmann, Bongshin Lee, Ulrich Von Zadow, Anthony Tang
Research Collection School Of Computing and Information Systems
Interactive tabletops and surfaces (ITSs) provide rich opportunities for data visualization and analysis and consequently are used increasingly in such settings. A research agenda of some of the most pressing challenges related to visualization on ITSs emerged from discussions with researchers and practitioners in human-computer interaction, computer-supported collaborative work, and a variety of visualization fields at the 2011 Workshop on Data Exploration for Interactive Surfaces (Dexis 2011)
Image Collection Summarization Via Dictionary Learning For Sparse Representation,
2013
University of North Carolina at Charlotte
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, …
Confidence Weighted Mean Reversion Strategy For Online Portfolio Selection,
2013
Nanyang Technological University
Confidence Weighted Mean Reversion Strategy For Online Portfolio Selection, Bin Li, Steven C. H. Hoi, Peilin Zhao, Vivekanand Gopalkrishnan
Research Collection School Of Computing and Information Systems
Online portfolio selection has been attracting increasing attention from the data mining and machine learning communities. All existing online portfolio selection strategies focus on the first order information of a portfolio vector, though the second order information may also be beneficial to a strategy. Moreover, empirical evidence shows that relative stock prices may follow the mean reversion property, which has not been fully exploited by existing strategies. This article proposes a novel online portfolio selection strategy named Confidence Weighted Mean Reversion (CWMR). Inspired by the mean reversion principle in finance and confidence weighted online learning technique in machine learning, CWMR …
A Self-Training Framework For Automatic Identification Of Exploratory Dialogue,
2013
Singapore Management University
A Self-Training Framework For Automatic Identification Of Exploratory Dialogue, Zhongyu Wei, Yulan He, Simon Shum, Rebecca Ferguson, Wei Gao, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
The dramatic increase in online learning materials over the last decade has made it difficult for individuals to locate information they need. Until now, researchers in the field of Learning Analytics have had to rely on the use of manual approaches to identify exploratory dialogue. This type of dialogue is desirable in online learning environments, since training learners to use it has been shown to improve learning outcomes. In this paper, we frame the problem of exploratory dialogue detection as a binary classification task, classifying a given contribution to an online dialogue as exploratory or non-exploratory. We propose a self-training …
Robust Image Analysis With Sparse Representation On Quantized Visual Features,
2013
Chinese Academy of Sciences
Robust Image Analysis With Sparse Representation On Quantized Visual Features, Bingkun Bao, Guangyu Zhu, Jialie Shen, Shuicheng Yan
Research Collection School Of Computing and Information Systems
Recent techniques based on Sparse Representation (SR) have demonstrated promising performance on high-level visual recognition, exemplified by the high-accuracy face recognition under occlusions and other sparse corruptions [1]. Most research in this area has focused on classification algorithms using raw image pixels, and very few have been proposed to utilize the quantized visual features, such as the popular Bagof- Words (BOW) feature abstraction. In such cases, besides the inherent quantization errors, ambiguity associated with visual word assignment and mis-detection of feature points due to factors such as visual occlusions and noises, constitutes the major causes to the dense corruptions of …
Semi-Supervised Heterogeneous Fusion For Multimedia Data Co-Clustering,
2013
Singapore Management University
Semi-Supervised Heterogeneous Fusion For Multimedia Data Co-Clustering, Lei Meng, Ah-Hwee Tan, Dong Xu
Research Collection School Of Computing and Information Systems
Co-clustering is a commonly used technique for tapping the rich meta-information of multimedia web documents, including category, annotation, and description, for associative discovery. However, most co-clustering methods proposed for heterogeneous data do not consider the representation problem of short and noisy text and their performance is limited by the empirical weighting of the multi-modal features. In this paper, we propose a generalized form of Heterogeneous Fusion Adaptive Resonance Theory, called GHF-ART, for co-clustering of large-scale web multimedia documents. By extending the two-channel Heterogeneous Fusion ART (HF-ART) to multiple channels, GHF-ART is designed to handle multimedia data with an arbitrarily rich …
Spoons: Netflix Outage Detection Using Microtext Classification,
2013
California Polytechnic State University, San Luis Obispo
Spoons: Netflix Outage Detection Using Microtext Classification, Eriq A. Augusitne
Master's Theses
Every week there are over a billion new posts to Twitter services and many of those messages contain feedback to companies about their services. One company that recognizes this unused source of information is Netflix. That is why Netflix initiated the development of a system that lets them respond to the millions of Twitter and Netflix users that are acting as sensors and reporting all types of user visible outages. This system enhances the feedback loop between Netflix and its customers by increasing the amount of customer feedback that Netflix receives and reducing the time it takes for Netflix to …
Data Mining The Functional Characterizations Of Proteins To Predict Their Cancer-Relatedness,
2013
University of Nebraska-Lincoln
Data Mining The Functional Characterizations Of Proteins To Predict Their Cancer-Relatedness, Peter Revesz, Christopher Assi
School of Computing: Faculty Publications
This paper considers two types of protein data. First, data about protein function described in a number of ways, such as, GO terms and PFAM families. Second, data about whether individual proteins are experimentally associated with cancer by an anomalous elevation or lowering of their expressions within cancerous cells. We combine these two types of protein data and test whether the first type of data, that is, the functional descriptors, can predict the second type of data, that is, cancer-relatedness. By using data mining and machine learning, we derive a classifier algorithm that using only GO term and PFAM family …
Guest Editorial: Selected Papers From Icimcs 2011,
2013
Singapore Management University
Guest Editorial: Selected Papers From Icimcs 2011, Chong-Wah Ngo, Changsheng Xu, Xiao Wu, Abdulmotaleb El Saddik
Research Collection School Of Computing and Information Systems
International Conference on Internet Multimedia Computing and Services (ICIMCS) is an annual conference sponsored by ACM SIGMM China Chapter. The conference is especially interested in the latest technologies and applications that deal with the web-scale processing and management of heterogeneous data from the Internet for multimedia computing and service. ICIMCS 2011 held in Chengdu, China— the ancient hometown of lovely panda. The conference has attracted around 80 participants, including researchers from academia and industries across ten countries/regions, for sharing their recent works in the topics ranging from visual information analysis and mining, query processing and search, multimedia privacy and security.
K-Pop Live: Social Networking & Language Learning Platform,
2013
Singapore Management University
K-Pop Live: Social Networking & Language Learning Platform, Thomas Chua, Chin Leng Ong, Kian Ming Png, Aloysius Lau, Houston Toh, Feida Zhu, Kyong Jin Shim, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
K-Pop live is a social networking and language learning platform developed by an undergraduate student team from Singapore Management University. K-Pop live aims to combine social media together with gamification to promote Korean culture. It consolidates all relevant Tweets from Twitter as well as videos from YouTube. The platform allows the user to connect with his friends who share similar interests in terms of K-pop artists and music.
Online Multiple Kernel Classification,
2013
Singapore Management University
Online Multiple Kernel Classification, Steven C. H. Hoi, Rong Jin, Peilin Zhao, Tianbao Yang
Research Collection School Of Computing and Information Systems
Although both online learning and kernel learning have been studied extensively in machine learning, there is limited effort in addressing the intersecting research problems of these two important topics. As an attempt to fill the gap, we address a new research problem, termed Online Multiple Kernel Classification (OMKC), which learns a kernel-based prediction function by selecting a subset of predefined kernel functions in an online learning fashion. OMKC is in general more challenging than typical online learning because both the kernel classifiers and the subset of selected kernels are unknown, and more importantly the solutions to the kernel classifiers and …
Online Multi-Modal Distance Learning For Scalable Multimedia Retrieval,
2013
Nanyang Technological University
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 …
Synthetic Controllable Turbulence Using Robust Second Vorticity Confinement,
2013
Singapore Management University
Synthetic Controllable Turbulence Using Robust Second Vorticity Confinement, Shengfeng He, Rynson W. H. Lau
Research Collection School Of Computing and Information Systems
Capturing fine details of turbulence on a coarse grid is one of the main tasks in real-time fluid simulation. Existing methods for doing this have various limitations. In this paper, we propose a new turbulence method that uses a refined second vorticity confinement method, referred to as robust second vorticity confinement, and a synthesis scheme to create highly turbulent effects from coarse grid. The new technique is sufficiently stable to efficiently produce highly turbulent flows, while allowing intuitive control of vortical structures. Second vorticity confinement captures and defines the vortical features of turbulence on a coarse grid. However, due to …
What Kind Of #Conversation Is Twitter? Mining #Psycholinguistic Cues For Emergency Coordination,
2013
Wright State University - Main Campus
What Kind Of #Conversation Is Twitter? Mining #Psycholinguistic Cues For Emergency Coordination, Hemant Purohit, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John M. Flach, Shreyansh Bhatt
Kno.e.sis Publications
The information overload created by social media messages in emergency situations challenges response organizations to find targeted content and users. We aim to select useful messages by detecting the presence of conversation as an indicator of coordinated citizen action. Using simple linguistic indicators associated with conversation analysis in social science, we model the presence of conversation in the communication landscape of Twitter in a large corpus of 1.5M tweets for various disaster and non-disaster events spanning different periods, lengths of time and varied social significance. Within Replies, Retweets and tweets that mention other Twitter users, we found that domain-independent, linguistic …
Stock Market Prediction Without Sentiment Analysis: Using A Web-Traffic Based Classifier And User-Level Analysis,
2013
Technological University Dublin
Stock Market Prediction Without Sentiment Analysis: Using A Web-Traffic Based Classifier And User-Level Analysis, Pierpaolo Dondio
Conference papers
This paper provides further evidence on the predictive power of online community traffic with regard to stock prices. Using the largest dataset to date, spanning 8 years and almost the complete set of SP500 stocks, we train a classifier using a set of features entirely extracted from web-traffic data of financial online communities. The classifier is shown to outperform the predictive power of a baseline classifier solely based on price time-series, and to have similar performances as the classifier built considering price and traffic features together. The best predictive performances are achieved when information about stock capitalization is coupled with …
