Triad-Based Role Discovery For Large Social Systems,
2014
Wright State University - Main Campus
Triad-Based Role Discovery For Large Social Systems, Derek Doran
Kno.e.sis Publications
The social role of a participant in a social system conceptualizes the circumstances under which she chooses to interact with others, making their discovery and analysis important for theoretical and practical purposes. In this paper, we propose a methodology to detect such roles by utilizing the conditional triad censuses of ego-networks. These censuses are a promising tool for social role extraction because they capture the degree to which basic social forces push upon a user to interact with others in a system. Clusters of triad censuses, inferred from network samples that preserve local structural properties, define the social roles. The …
Design Of Randomized Experiments In Networks,
2014
Chapman University
Design Of Randomized Experiments In Networks, Dylan Walker, Lev Muchnik
Business Faculty Articles and Research
Over the last decade, the emergence of pervasive online and digitally enabled environments has created a rich source of detailed data on human behavior. Yet, the promise of big data has recently come under fire for its inability to separate correlation from causation-to derive actionable insights and yield effective policies. Fortunately, the same online platforms on which we interact on a day-to-day basis permit experimentation at large scales, ushering in a new movement toward big experiments. Randomized controlled trials are the heart of the scientific method and when designed correctly provide clean causal inferences that are robust and reproducible. However, …
"Be Our Guest:" Crafting A Magical Client Experience,
2014
Valparaiso University
"Be Our Guest:" Crafting A Magical Client Experience, Rebecca Klein, Kevin Steele
Information Technology Faculty and Staff Publications
The Client Services team of Valparaiso University’s IT department found inspiration in Disney’s guest service models and has been building a culture of superior service throughout IT. Come along on a magic carpet ride to discover how this new world is transforming delivery of technological services to the campus. From Help Desk to training to assessment, we are increasing satisfaction levels among campus constituents as we meet their needs. We will show how we created a guest service compass that guides our decision-making and service delivery. Further, we will share areas where we learned we were creating our own obstacles …
Discovering Perceptions In Online Social Media: A Probabilistic Approach,
2014
Wright State University - Main Campus
Discovering Perceptions In Online Social Media: A Probabilistic Approach, Derek Doran, Swapna S. Gokhale, Aldo Dagnino
Kno.e.sis Publications
People across the world habitually turn to online social media to share their experiences, thoughts, ideas, and opinions as they go about their daily lives. These posts collectively contain a wealth of insights into how masses perceive their surroundings. Therefore, extracting people’s perceptions from social media posts can provide valuable information about pertinent issues such as public transportation, emergency conditions, and even reactions to political actions or other activities. This paper proposes a novel approach to extract such perceptions from a corpus of social media posts originating from a given broad geographical region. The approach divides the broad region into …
Online Information Searching For Cardiovascular Diseases: An Analysis Of Mayo Clinic Search Query Logs,
2014
Wright State University - Main Campus
Online Information Searching For Cardiovascular Diseases: An Analysis Of Mayo Clinic Search Query Logs, Ashutosh Sopan Jadhav, Amit P. Sheth, Jyotishman Pathak
Kno.e.sis Publications
Since the early 2000’s, Internet usage for health information searching has increased significantly. Studying search queries can help us to understand users “information need” and how do they formulate search queries (“expression of information need”). Although cardiovascular diseases (CVD) affect a large percentage of the population, few studies have investigated how and what users search for CVD. We address this knowledge gap in the community by analyzing a large corpus of 10 million CVD related search queries from MayoClinic.com. Using UMLS MetaMap and UMLS semantic types/concepts, we developed a rule-based approach to categorize the queries into 14 health categories. We …
An Analysis Of Mayo Clinic Search Query Logs For Cardiovascular Diseases,
2014
Wright State University - Main Campus
An Analysis Of Mayo Clinic Search Query Logs For Cardiovascular Diseases, Ashutosh Sopan Jadhav, Amit P. Sheth, Jyotishman Pathak
Kno.e.sis Publications
Increasingly, individuals are taking active participation in learning and managing their health by leveraging online resources. Understanding online health information searching behavior can help us to study what health topics users search for and how search queries are formulated. In this work, we analyzed 10 million cardiovascular diseases (CVD) related search queries from MayoClinic.com. We performed semantic analysis on the queries using UMLS MetaMap and analyzed structural and textual properties as well as linguistic characteristics of the queries.
Combining Multiple Kernel Methods On Riemannian Manifold For Emotion Recognition In The Wild,
2014
Singapore Management University
Combining Multiple Kernel Methods On Riemannian Manifold For Emotion Recognition In The Wild, M. Liu, R. Wang, S. Li, S. Shan, Zhiwu Huang, X. Chen
Research Collection School Of Computing and Information Systems
In this paper, we present the method for our submission to the Emotion Recognition in the Wild Challenge (EmotiW 2014). The challenge is to automatically classify the emotions acted by human subjects in video clips under realworld environment. In our method, each video clip can be represented by three types of image set models (i.e. linear subspace, covariance matrix, and Gaussian distribution) respectively, which can all be viewed as points residing on some Riemannian manifolds. Then different Riemannian kernels are employed on these set models correspondingly for similarity/distance measurement. For classification, three types of classifiers, i.e. kernel SVM, logistic regression, …
Client/Server Data Synchronization In Ios Development,
2014
East Tennessee State University
Client/Server Data Synchronization In Ios Development, Dmitry Tumanov
Undergraduate Honors Theses
Electronic gadgets such as touchpads and smartphones are becoming more popular in business and everyday life. The main advantage of mobile devices over personal computers is their portability. Cellular data plans allow Internet access without having permanent access point. There is a number of web-based applications available for gadgets. The primary goal of these apps is to provide their services through constant Internet access. However, it may affect the operation of both devices and applications. The objective of this thesis is to find a better way of client/server data synchronization in iOS development that can reduce the negative consequences of …
Player Acceptance Of Human Computation Games: An Aesthetic Perspective,
2014
Nanyang Technological University, Singapore
Player Acceptance Of Human Computation Games: An Aesthetic Perspective, Xiaohui Wang, Dion Hoe Lian Goh, Ee Peng Lim, Adrian Wei Liang Vu
Research Collection School Of Computing and Information Systems
Human computation games (HCGs) are applications that use games to harness human intelligence to perform computations that cannot be effectively done by software systems alone. Despite their increasing popularity, insufficient research has been conducted to examine the predictors of player acceptance for HCGs. In particular, prior work underlined the important role of game enjoyment in predicting acceptance of entertainment technology without specifying its driving factors. This study views game enjoyment through a taxonomy of aesthetic experiences and examines the effect of aesthetic experience, usability and information quality on player acceptance of HCGs. Results showed that aesthetic experience and usability were …
Exploiting Geographical Neighborhood Characteristics For Location Recommendation,
2014
Nanyang Technological University
Exploiting Geographical Neighborhood Characteristics For Location Recommendation, Yong Liu, Wei Wei, Aixin Sun, Chunyan Miao
Research Collection School Of Computing and Information Systems
Geographical characteristics derived from the historical check-in data have been reported effective in improving location recommendation accuracy. However, previous studies mainly exploit geographical characteristics from a user’s perspective, via modeling the geographical distribution of each individual user’s check-ins. In this paper, we are interested in exploiting geographical characteristics from a location perspective, by modeling the geographical neighborhood of a location. The neighborhood is modeled at two levels: the instance-level neighborhood defined by a few nearest neighbors of the location, and the region-level neighborhood for the geographical region where the location exists. We propose a novel recommendation approach, namely Instance-Region Neighborhood …
Online Passive Aggressive Active Learning And Its Applications,
2014
Singapore Management University
Online Passive Aggressive Active Learning And Its Applications, Jing Lu, Peilin Zhao, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
We investigate online active learning techniques for classification tasks in data stream mining applications. Unlike traditional learning approaches (either batch or online learning) that often require to request the class label of each incoming instance, online active learning queries only a subset of informative incoming instances to update the classification model, which aims to maximize classification performance using minimal human labeling effort during the entire online stream data mining task. In this paper, we present a new family of algorithms for online active learning called Passive-Aggressive Active (PAA) learning algorithms by adapting the popular Passive-Aggressive algorithms in an online active …
Perspectives On Task Ownership In Mobile Operating System Development [Invited Talk],
2014
Singapore Management University
Perspectives On Task Ownership In Mobile Operating System Development [Invited Talk], Subhajit Datta
Research Collection School Of Computing and Information Systems
There can be little contention about Stroustrup's epigrammatic remark: our civilization runs on software. However a caveat is increasingly due, much of the software that runs our civilization, runs on mobile devices today. Mobile operating systems have come to play a preeminent role in the ubiquity and utility of such devices. The development ecosystem of Android - one of the most popular mobile operating systems - presents an interesting context for studying whether and how collaboration dynamics in mobile development differ from conventional software development. In this paper, we examine factors that influence task ownership in Android development. Our results …
Generative Modeling Of Entity Comparisons In Text,
2014
St Petersburg State University
Generative Modeling Of Entity Comparisons In Text, Maksim Tkachenko, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Users frequently rely on online reviews for decision making. In addition to allowing users to evaluate the quality of individual products, reviews also support comparison shopping. One key user activity is to compare two (or more) products based on a specific aspect. However, making a comparison across two different reviews, written by different authors, is not always equitable due to the different standards and preferences of individual authors. Therefore, we focus instead on comparative sentences, whereby two products are compared directly by a review author within a single sentence. We study the problem of comparative relation mining. Given a set …
Historical Traffic-Tolerant Paths In Road Networks,
2014
Hong Kong Polytechnic University
Historical Traffic-Tolerant Paths In Road Networks, Pui Hang Li, Man Lung Yiu, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
Historical traffic information is valuable for transportation analysis and planning, as well as for route search services. In view of these applications, we propose the k traffic-tolerant paths problem (TTP) on road networks, which takes a source-destination pair and historical traffic information as input, and returns k paths that minimize the aggregate (historical) travel time. Unlike the shortest path problem, the TTP problem has a combinatorial search space that renders the optimal solution expensive to compute. We propose an exact algorithm and a heuristic algorithm for this problem. Experiments on real traffic data demonstrate the effectiveness of TTP paths and …
Modloc: Localizing Multiple Objects In Dynamic Indoor Environment,
2014
Singapore Management University
Modloc: Localizing Multiple Objects In Dynamic Indoor Environment, Xiaonan Guo, Dian Zhang, Kaishun Wu, Lionel M. Ni
Research Collection School Of Computing and Information Systems
Radio frequency (RF) based technologies play an important role in indoor localization, since Radio Signal Strength (RSS) can be easily measured by various wireless devices without additional cost. Among these, radio map based technologies (also referred as fingerprinting technologies) are attractive due to high accuracy and easy deployment. However, these technologies have not been extensively applied on real environment for two fatal limitations. First, it is hard to localize multiple objects. When the number of target objects is unknown, constructing a radio map of multiple objects is almost impossible. Second, environment changes will generate different multipath signals and severely disturb …
An Ecological Model For Digital Platforms Maintenance And Evolution,
2014
Guido Carli University
An Ecological Model For Digital Platforms Maintenance And Evolution, Paolo Rocchi, Paolo Spagnoletti, Subhajit Datta
Research Collection School Of Computing and Information Systems
The maintenance of software products has been studied extensively in both software engineering and management information systems. Such studies are mainly focused on the activities that take place prior to starting the maintenance phase. Their contribution is either related to the improvement of software quality or to validating contingency models for reducing maintenance efforts. The continuous maintenance philosophy suggests to shift the attention within the maintenance phase for better coping with the evolutionary trajectories of digital platforms. In this paper, we examine the maintenance process of a digital platform from the perspective of the software vendor. Based on our empirical …
Developer Involvement Considered Harmful? An Empirical Examination Of Android Bug Resolution Times,
2014
Singapore Management University
Developer Involvement Considered Harmful? An Empirical Examination Of Android Bug Resolution Times, Subhajit Datta, Proshanta Sarkar, Subhashis Majumder
Research Collection School Of Computing and Information Systems
In large scale software development ecosystems, there is a common perception that higher developer involvement leads to faster resolution of bugs. This is based on conjectures around more ``eyeballs" making bugs "shallow" -- whose validity and applicability are not without dispute. In this paper, we posit that the level of developer attention as well as its extent of diversity influence how quickly bugs get resolved. We report results from a study of 1,000+ Android bugs. We find statistically significant evidence that attention and diversity have contrasting relationships with the resolution time of bugs, even after controlling for factors such as …
On Joint Modeling Of Topical Communities And Personal Interest In Microblogs,
2014
Singapore Management University
On Joint Modeling Of Topical Communities And Personal Interest In Microblogs, Tuan-Anh Hoang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
In this paper, we propose the Topical Communities and Personal Interest (TCPI) model for simultaneously modeling topics, topical communities, and users’ topical interests in microblogging data. TCPI considers different topical communities while differentiating users’ personal topical interests from those of topical communities, and learning the dependence of each user on the affiliated communities to generate content. This makes TCPI different from existing models that either do not consider the existence of multiple topical communities, or do not differentiate between personal and community’s topical interests. Our experiments on two Twitter datasets show that TCPI can effectively mine the representative topics for …
Online Transfer Learning,
2014
Institute for Infocomm Research, Singapore
Online Transfer Learning, Peilin Zhao, Steven C. H. Hoi, Jialei Wang, Bin Li
Research Collection School Of Computing and Information Systems
This paper investigates a new machine learning framework of Online Transfer Learning (OTL), which aims to attack an online learning task on a target domain by transferring knowledge from some source domain. We do not assume data in the target domain follows the same distribution as that in the source domain, and the motivation of our work is to enhance a supervised online learning task on a target domain by exploiting the existing knowledge that had been learnt from training data in source domains. OTL is in general a challenging problem since data in both source and target domains not …
Deep Learning For Content-Based Image Retrieval: A Comprehensive Study,
2014
Chinese Academy of Sciences
Deep Learning For Content-Based Image Retrieval: A Comprehensive Study, Ji Wan, Dayong Wang, Steven C. H. Hoi, Pengcheng Wu, Jianke Zhu, Yongdong Zhang, Jintao Li
Research Collection School Of Computing and Information Systems
Learning effective feature representations and similarity measures are crucial to the retrieval performance of a content-based image retrieval (CBIR) system. Despite extensive research efforts for decades, it remains one of the most challenging open problems that considerably hinders the successes of real-world CBIR systems. The key challenge has been attributed to the well-known "semantic gap" issue that exists between low-level image pixels captured by machines and high-level semantic concepts perceived by human. Among various techniques, machine learning has been actively investigated as a possible direction to bridge the semantic gap in the long term. Inspired by recent successes of deep …
