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Articles 3391 - 3420 of 7334
Full-Text Articles in Computer Sciences
Maximizing The Probability Of Arriving On Time: A Practical Q-Learning Method, Zhiguang Cao, Hongliang Guo, Jie Zhang, Frans Oliehoek, Ulrich Fastenrath
Maximizing The Probability Of Arriving On Time: A Practical Q-Learning Method, Zhiguang Cao, Hongliang Guo, Jie Zhang, Frans Oliehoek, Ulrich Fastenrath
Research Collection School Of Computing and Information Systems
The stochastic shortest path problem is of crucial importance for the development of sustainable transportation systems. Existing methods based on the probability tail model seek for the path that maximizes the probability of arriving at the destination before a deadline. However, they suffer from low accuracy and/or high computational cost. We design a novel Q-learning method where the converged Q-values have the practical meaning as the actual probabilities of arriving on time so as to improve accuracy. By further adopting dynamic neural networks to learn the value function, our method can scale well to large road networks with arbitrary deadlines. …
Recurrent Neural Networks With Auxiliary Labels For Cross-Domain Opinion Target Extraction, Ying Ding, Jianfei Yu, Jing Jiang
Recurrent Neural Networks With Auxiliary Labels For Cross-Domain Opinion Target Extraction, Ying Ding, Jianfei Yu, Jing Jiang
Research Collection School Of Computing and Information Systems
Opinion target extraction is a fundamental task in opinion mining. In recent years, neural network based supervised learning methods have achieved competitive performance on this task. However, as with any supervised learning method, neural network based methods for this task cannot work well when the training data comes from a different domain than the test data. On the other hand, some rule-based unsupervised methods have shown to be robust when applied to different domains. In this work, we use rule-based unsupervised methods to create auxiliary labels and use neural network models to learn a hidden representation that works well for …
Streaming Classification With Emerging New Class By Class Matrix Sketching, Xin Mu, Feida Zhu, Juan Du, Ee-Peng Lim, Zhi-Hua Zhou
Streaming Classification With Emerging New Class By Class Matrix Sketching, Xin Mu, Feida Zhu, Juan Du, Ee-Peng Lim, Zhi-Hua Zhou
Research Collection School Of Computing and Information Systems
Streaming classification with emerging new class is an important problem of great research challenge and practical value. In many real applications, the task often needs to handle large matrices issues such as textual data in the bag-of-words model and large-scale image analysis. However, the methodologies and approaches adopted by the existing solutions, most of which involve massive distance calculation, have so far fallen short of successfully addressing a real-time requested task. In this paper, the proposed method dynamically maintains two low-dimensional matrix sketches to 1) detect emerging new classes; 2) classify known classes; and 3) update the model in the …
Discovering Burst Patterns Of Burst Topic In Twitter, Guozhong Dong, Wu Yang, Feida Zhu, Wei Wang
Discovering Burst Patterns Of Burst Topic In Twitter, Guozhong Dong, Wu Yang, Feida Zhu, Wei Wang
Research Collection School Of Computing and Information Systems
Twitter has become one of largest social networks for users to broadcast burst topics. There have been many studies on how to detect burst topics. However, mining burst patterns in burst topics has not been solved by the existing works. In this paper, we investigate the problem of mining burst patterns of burst topic in Twitter. A burst topic user graph model is proposed, which can represent the topology structure of burst topic propagation across a large number of Twitter users. Based on the model, hierarchical clustering is applied to cluster burst topics and reveal burst patterns from the macro …
Detecting Similar Repositories On Github, Yun Zhang, David Lo, Pavneet Singh Kochhar, Xin Xia, Quanlai Li, Jianling Sun
Detecting Similar Repositories On Github, Yun Zhang, David Lo, Pavneet Singh Kochhar, Xin Xia, Quanlai Li, Jianling Sun
Research Collection School Of Computing and Information Systems
GitHub contains millions of repositories among which many are similar with one another (i.e., having similar source codes or implementing similar functionalities). Finding similar repositories on GitHub can be helpful for software engineers as it can help them reuse source code, build prototypes, identify alternative implementations, explore related projects, find projects to contribute to, and discover code theft and plagiarism. Previous studies have proposed techniques to detect similar applications by analyzing API usage patterns and software tags. However, these prior studies either only make use of a limited source of information or use information not available for projects on GitHub. …
Collaboration Trumps Homophily In Urban Mobile Crowd-Sourcing, Thivya Kandappu, Archan Misra, Randy Tandriansyah Daratan
Collaboration Trumps Homophily In Urban Mobile Crowd-Sourcing, Thivya Kandappu, Archan Misra, Randy Tandriansyah Daratan
Research Collection School Of Computing and Information Systems
This paper establishes the power of dynamic collaborative task completion among workers for urban mobile crowdsourcing. Collaboration is defined via the notion of peer referrals, whereby a worker who has accepted a location-specific task, but is unlikely to visit that location, offloads the task to a willing friend. Such a collaborative framework might be particularly useful for task bundles, especially for bundles that have higher geographic dispersion. The challenge, however, comes from the high similarity observed in the spatiotemporal pattern of task completion among friends. Using extensive real-world crowd-sourcing studies conducted over 7 weeks and 1000+ workers on a campus-based …
Harnessing Twitter To Support Serendipitous Learning Of Developers, Abhabhisheksh Sharma, Yuan Tian, Agus Sulistya, David Lo, Aiko Yamashita
Harnessing Twitter To Support Serendipitous Learning Of Developers, Abhabhisheksh Sharma, Yuan Tian, Agus Sulistya, David Lo, Aiko Yamashita
Research Collection School Of Computing and Information Systems
Developers often rely on various online resources, such as blogs, to keep themselves up-to-date with the fast pace at which software technologies are evolving. Singer et al. found that developers tend to use channels such as Twitter to keep themselves updated and support learning, often in an undirected or serendipitous way, coming across things that they may not apply presently, but which should be helpful in supporting their developer activities in future. However, identifying relevant and useful articles among the millions of pieces of information shared on Twitter is a non-trivial task. In this work to support serendipitous discovery of …
Crowdsensing And Analyzing Micro-Event Tweets For Public Transportation Insights, Thoong Hoang, Pei Hua (Xu Peihua) Cher, Philips Kokoh Prasetyo, Ee-Peng Lim
Crowdsensing And Analyzing Micro-Event Tweets For Public Transportation Insights, Thoong Hoang, Pei Hua (Xu Peihua) Cher, Philips Kokoh Prasetyo, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Efficient and commuter friendly public transportation system is a critical part of a thriving and sustainable city. As cities experience fast growing resident population, their public transportation systems will have to cope with more demands for improvements. In this paper, we propose a crowdsensing and analysis framework to gather and analyze realtime commuter feedback from Twitter. We perform a series of text mining tasks identifying those feedback comments capturing bus related micro-events; extracting relevant entities; and, predicting event and sentiment labels. We conduct a series of experiments involving more than 14K labeled tweets. The experiments show that incorporating domain knowledge …
Why And How Developers Fork What From Whom In Github, Jing Jiang, David Lo, Jiahuan He, Xin Xia, Pavneet Singh Kochhar, Li Zhang
Why And How Developers Fork What From Whom In Github, Jing Jiang, David Lo, Jiahuan He, Xin Xia, Pavneet Singh Kochhar, Li Zhang
Research Collection School Of Computing and Information Systems
Forking is the creation of a new software repository by copying another repository. Though forking is controversial in traditional open source software (OSS) community, it is encouraged and is a built-in feature in GitHub. Developers freely fork repositories, use codes as their own and make changes. A deep understanding of repository forking can provide important insights for OSS community and GitHub. In this paper, we explore why and how developers fork what from whom in GitHub. We collect a dataset containing 236,344 developers and 1,841,324 forks. We make surveys, and analyze programming languages and owners of forked repositories. Our main …
Attribute-Based Secure Messaging In The Public Cloud, Zhi Yuan Poh, Hui Cui, Robert H. Deng, Yingjiu Li
Attribute-Based Secure Messaging In The Public Cloud, Zhi Yuan Poh, Hui Cui, Robert H. Deng, Yingjiu Li
Research Collection School Of Computing and Information Systems
Messaging systems operating within the public cloud are gaining popularity. To protect message confidentiality from the public cloud including the public messaging servers, we propose to encrypt messages in messaging systems using Attribute-Based Encryption (ABE). ABE is an one-to-many public key encryption system in which data are encrypted with access policies and only users with attributes that satisfy the access policies can decrypt the ciphertexts, and hence is considered as a promising solution for realizing expressive and fine-grained access control of encrypted data in public servers. Our proposed system, called Attribute-Based Secure Messaging System with Outsourced Decryption (ABSM-OD), has three …
Active Video Summarization: Customized Summaries Via On-Line Interaction With The User, Ana Garcia Del Molino, Xavier Boix, Joo-Hwee Lim, Ah-Hwee Tan
Active Video Summarization: Customized Summaries Via On-Line Interaction With The User, Ana Garcia Del Molino, Xavier Boix, Joo-Hwee Lim, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
To facilitate the browsing of long videos, automatic video summarization provides an excerpt that represents its content. In the case of egocentric and consumer videos, due to their personal nature, adapting the summary to specific user’s preferences is desirable. Current approaches to customizable video summarization obtain the user’s preferences prior to the summarization process. As a result, the user needs to manually modify the summary to further meet the preferences. In this paper, we introduce Active Video Summarization (AVS), an interactive approach to gather the user’s preferences while creating the summary. AVS asks questions about the summary to update it …
Using An Online Tutorial To Teach Rea Data Modeling In Accounting Information Systems Courses, Poh Sun Seow, Pan, Gary
Using An Online Tutorial To Teach Rea Data Modeling In Accounting Information Systems Courses, Poh Sun Seow, Pan, Gary
Research Collection School Of Accountancy
Online learning has been gaining widespread adoption due to its successin enhancing student-learning outcomes and improving student t academicperformance. This paper describes an online tutorial to teach resource-event-agent(REA) data modeling in an undergraduate accounting information systems course.The REA online tutorial reflects a self-study application designed to helpstudents improve their understanding of the REA data model. As such, thetutorial acts as a supplement to lectures by reinforcing the concepts andincorporating practices to assess student understanding. Instructors can accessthe REA online tutorial at http://smu.asg/rea. An independent survey by the University’sCentre for Teaching Excellence found a significant increase in students’perceived knowledge of REA …
Soal: Second-Order Online Active Learning, Shuji Hao, Peilin Zhao, Jing Lu, Steven C. H. Hoi, Chunyan Miao, Chi Zhang
Soal: Second-Order Online Active Learning, Shuji Hao, Peilin Zhao, Jing Lu, Steven C. H. Hoi, Chunyan Miao, Chi Zhang
Research Collection School Of Computing and Information Systems
This paper investigates the problem of online active learning for training classification models from sequentially arriving data. This is more challenging than conventional online learning tasks since the learner not only needs to figure out how to effectively update the classifier but also needs to decide when is the best time to query the label of an incoming instance given limited label budget. The existing online active learning approaches are often based on first-order online learning methods which generally fall short in slow convergence rate and suboptimal exploitation of available information when querying the labeled data. To overcome the limitations, …
Let’S Try Something New: Service Learning In Boise State's Computer Science Department, Daniel Kondratyuk
Let’S Try Something New: Service Learning In Boise State's Computer Science Department, Daniel Kondratyuk
International Journal of Undergraduate Community Engagement
In this article I explain how a group of Computer Science students at Boise State University participated in a new service learning project. I provide a few testimonials on the students’ experiences and describe the rewarding aspects of service learning in the greater Computer Science community.
An Annotated Corpus With Nanomedicine And Pharmacokinetic Parameters, Nastassja Lewinski, Ivan Jimenez, Bridget Mcinnes
An Annotated Corpus With Nanomedicine And Pharmacokinetic Parameters, Nastassja Lewinski, Ivan Jimenez, Bridget Mcinnes
Chemical and Life Science Engineering Publications
A vast amount of data on nanomedicines is being generated and published, and natural language processing (NLP) approaches can automate the extraction of unstructured text-based data. Annotated corpora are a key resource for NLP and information extraction methods which employ machine learning. Although corpora are available for pharmaceuticals, resources for nanomedicines and nanotechnology are still limited. To foster nanotechnology text mining (NanoNLP) efforts, we have constructed a corpus of annotated drug product inserts taken from the US Food and Drug Administration’s Drugs@FDA online database. In this work, we present the development of the Engineered Nanomedicine Database corpus to support the …
Parsing Metamap Files In Hadoop, Amy Olex, Alberto Cano, Bridget T. Mcinnes
Parsing Metamap Files In Hadoop, Amy Olex, Alberto Cano, Bridget T. Mcinnes
Computer Science Publications
The UMLS::Association CUICollector module identifies UMLS Concept Unique Identifier bigrams and their frequencies in a biomedical text corpus. CUICollector was re-implemented in Hadoop MapReduce to improve algorithm speed, flexibility, and scalability. Evaluation of the Hadoop implementation compared to the serial module produced equivalent results and achieved a 28x speedup on a single-node Hadoop system.
Road Accidents Bigdata Mining And Visualization Using Support Vector Machines, Usha Lokala, Srinivas Nowduri, Prabhakar K. Sharma
Road Accidents Bigdata Mining And Visualization Using Support Vector Machines, Usha Lokala, Srinivas Nowduri, Prabhakar K. Sharma
Kno.e.sis Publications
Useful information has been extracted from the road accident data in United Kingdom (UK), using data analytics method, for avoiding possible accidents in rural and urban areas. This analysis make use of several methodologies such as data integration, support vector machines (SVM), correlation machines and multinomial goodness. The entire datasets have been imported from the traffic department of UK with due permission. The information extracted from these huge datasets forms a basis for several predictions, which in turn avoid unnecessary memory lapses. Since data is expected to grow continuously over a period of time, this work primarily proposes a new …
Relatedness-Based Multi-Entity Summarization, Kalpa Gunaratna, Amir Hossein Yazdavar, Krishnaprasad Thirunarayan, Amit Sheth, Gong Cheng
Relatedness-Based Multi-Entity Summarization, Kalpa Gunaratna, Amir Hossein Yazdavar, Krishnaprasad Thirunarayan, Amit Sheth, Gong Cheng
Kno.e.sis Publications
Representing world knowledge in a machine processable format is important as entities and their descriptions have fueled tremendous growth in knowledge-rich information processing platforms, services, and systems. Prominent applications of knowledge graphs include search engines (e.g., Google Search and Microsoft Bing), email clients (e.g., Gmail), and intelligent personal assistants (e.g., Google Now, Amazon Echo, and Apple’s Siri). In this paper, we present an approach that can summarize facts about a collection of entities by analyzing their relatedness in preference to summarizing each entity in isolation. Specifically, we generate informative entity summaries by selecting: (i) inter-entity facts that are similar and …
A Gamification Framework For Sensor Data Analytics, Alexandra L'Heureux, Katarina Grolinger, Wilson A. Higashino, Miriam A. M. Capretz
A Gamification Framework For Sensor Data Analytics, Alexandra L'Heureux, Katarina Grolinger, Wilson A. Higashino, Miriam A. M. Capretz
Electrical and Computer Engineering Publications
The Internet of Things (IoT) enables connected objects to capture, communicate, and collect information over the network through a multitude of sensors, setting the foundation for applications such as smart grids, smart cars, and smart cities. In this context, large scale analytics is needed to extract knowledge and value from the data produced by these sensors. The ability to perform analytics on these data, however, is highly limited by the difficulties of collecting labels. Indeed, the machine learning techniques used to perform analytics rely upon data labels to learn and to validate results. Historically, crowdsourcing platforms have been used to …
Semantic Inference On Clinical Documents: Combining Machine Learning Algorithms With An Inference Engine For Effective Clinical Diagnosis And Treatment, Shuo Yang, Ran Wei, Jingzhi Guo, Lida Xu
Semantic Inference On Clinical Documents: Combining Machine Learning Algorithms With An Inference Engine For Effective Clinical Diagnosis And Treatment, Shuo Yang, Ran Wei, Jingzhi Guo, Lida Xu
Information Technology & Decision Sciences Faculty Publications
Clinical practice calls for reliable diagnosis and optimized treatment. However, human errors in health care remain a severe issue even in industrialized countries. The application of clinical decision support systems (CDSS) casts light on this problem. However, given the great improvement in CDSS over the past several years, challenges to their wide-scale application are still present, including: 1) decision making of CDSS is complicated by the complexity of the data regarding human physiology and pathology, which could render the whole process more time-consuming by loading big data related to patients; and 2) information incompatibility among different health information systems (HIS) …
Qos Recommendation In Cloud Services, Xianrong Zheng, Li Da Xu, Sheng Chai
Qos Recommendation In Cloud Services, Xianrong Zheng, Li Da Xu, Sheng Chai
Information Technology & Decision Sciences Faculty Publications
As cloud computing becomes increasingly popular, cloud providers compete to offer the same or similar services over the Internet. Quality of service (QoS), which describes how well a service is performed, is an important differentiator among functionally equivalent services. It can help a firm to satisfy and win its customers. As a result, how to assist cloud providers to promote their services and cloud consumers to identify services that meet their QoS requirements becomes an important problem. In this paper, we argue for QoS-based cloud service recommendation, and propose a collaborative filtering approach using the Spearman coefficient to recommend cloud …
Industrial Wireless Sensor Networks 2016, Qindong Sun, Schancang Li, Shanshan Zhao, Hongjian Sun, Li Xu, Arumugam Nallamathan
Industrial Wireless Sensor Networks 2016, Qindong Sun, Schancang Li, Shanshan Zhao, Hongjian Sun, Li Xu, Arumugam Nallamathan
Information Technology & Decision Sciences Faculty Publications
The industrial wireless sensor network (IWSN) is the next frontier in the Industrial Internet of Things (IIoT), which is able to help industrial organizations to gain competitive advantages in industrial manufacturing markets by increasing productivity, reducing the costs, developing new products and services, and deploying new business models.
On The Security Of Nosql Cloud Database Services, Mohammad Ahmadian
On The Security Of Nosql Cloud Database Services, Mohammad Ahmadian
Electronic Theses and Dissertations
Processing a vast volume of data generated by web, mobile and Internet-enabled devices, necessitates a scalable and flexible data management system. Database-as-a-Service (DBaaS) is a new cloud computing paradigm, promising a cost-effective and scalable, fully-managed database functionality meeting the requirements of online data processing. Although DBaaS offers many benefits it also introduces new threats and vulnerabilities. While many traditional data processing threats remain, DBaaS introduces new challenges such as confidentiality violation and information leakage in the presence of privileged malicious insiders and adds new dimension to the data security. We address the problem of building a secure DBaaS for a …
The Relationship Between Technology Threat Avoidance And Innovation In Health Care Organizations, Melvin R. Fenner Jr
The Relationship Between Technology Threat Avoidance And Innovation In Health Care Organizations, Melvin R. Fenner Jr
Walden Dissertations and Doctoral Studies
Most leaders of healthcare delivery organizations have increased their rate of technological innovation, but some still struggle to keep pace with other industries. The problem addressed in this study was that senior leaders in some rural ambulatory healthcare facilities failed to innovate, even with recent healthcare technological innovations, which could lead to increased medical errors and a loss of efficiency. The purpose of the study was to examine if a relationship exists between the avoidance of technology threats by senior leaders in ambulatory healthcare organizations and the innovation propensity of the organization. Technology threat avoidance theory served as the theoretical …
The Challenges Of Implementing Bring Your Own Device, Leslie Deshield
The Challenges Of Implementing Bring Your Own Device, Leslie Deshield
Walden Dissertations and Doctoral Studies
Research conducted by Tech Pro (2014) indicated that the Bring Your Own Device (BYOD) concept is gaining momentum with 74% of organizations already having some BYOD program or planning to implement one. While BYOD offers several benefits, it also presents challenges that concern information technology leaders and information security managers. This correlational study used the systems theory framework to examine the relationship between information security managers' intentions, perceptions of security, and compliance regarding BYOD implementation. Participants of the study consisted of information security managers in the eastern United States who had obtained the Certified Information Systems Manager certification. Data was …
How Attitude Toward The Behavior, Subjective Norm, And Perceived Behavioral Control Affects Information Security Behavior Intention, David Philip Johnson
How Attitude Toward The Behavior, Subjective Norm, And Perceived Behavioral Control Affects Information Security Behavior Intention, David Philip Johnson
Walden Dissertations and Doctoral Studies
The education sector is at high risk for information security (InfoSec) breaches and in need of improved security practices. Achieving data protections cannot be through technical means alone. Addressing the human behavior factor is required. Security education, training, and awareness (SETA) programs are an effective method of addressing human InfoSec behavior. Applying sociobehavioral theories to InfoSec research provides information to aid IT security program managers in developing improved SETA programs. The purpose of this correlational study was to examine through the theoretical lens of the theory of planned behavior (TPB) how attitude toward the behavior (ATT), subjective norm (SN), and …
Examining The Behavioral Intention Of Individuals' Compliance With Information Security Policies, David A. Brown
Examining The Behavioral Intention Of Individuals' Compliance With Information Security Policies, David A. Brown
Walden Dissertations and Doctoral Studies
Target Corporation experienced an information security breach resulting in compromising customers' financial information. Management is responsible for implementing adequate information security policies that protect corporate data and minimize financial losses. The purpose of this experimental study was to examine the effect of a fear appeal communication on an individual's information security policy behavioral intention. The sample population involved information technology professionals randomly selected from the SurveyMonkey audience. A research model, developed using constructs from deterrence theory and protection motivation theory, became the structural model used for partial least squares-structural equation modeling (PLS-SEM) analysis of the survey response data, which indicated …
Strategies Information And Communication Technology Managers Use To Build Employee Competencies, Thulaganyo Arnold Rabogadi
Strategies Information And Communication Technology Managers Use To Build Employee Competencies, Thulaganyo Arnold Rabogadi
Walden Dissertations and Doctoral Studies
The World Economic Forum (WEF) found that Botswana's information and communication technology (ICT) networked readiness index (NRI) had declined from position 89 in 2012 to 104 in 2015. A decline in Botswana's ICT NRI resulted in a modest gross domestic product (GDP) growth increasing from 4.2% in 2012 to 5.0% in 2015. The purpose of this qualitative multiple case study was to explore strategies ICT service provider managers use to build employee competencies to address ICT infrastructure performance deficiencies. The target population for this study consisted of over 120 managers from 2 ICT service providers located in Gaborone and Francistown …
Security Strategies For Hosting Sensitive Information In The Commercial Cloud, Edward Steven Forde
Security Strategies For Hosting Sensitive Information In The Commercial Cloud, Edward Steven Forde
Walden Dissertations and Doctoral Studies
IT experts often struggle to find strategies to secure data on the cloud. Although current security standards might provide cloud compliance, they fail to offer guarantees of security assurance. The purpose of this qualitative case study was to explore the strategies used by IT security managers to host sensitive information in the commercial cloud. The study's population consisted of information security managers from a government agency in the eastern region of the United States. The routine active theory, developed by Cohen and Felson, was used as the conceptual framework for the study. The data collection process included IT security manager …
Information Technology Training To Promote Collaboration Among Multiple Generations, Gregg Foster
Information Technology Training To Promote Collaboration Among Multiple Generations, Gregg Foster
Walden Dissertations and Doctoral Studies
The decision to implement information technology (IT) initiatives to enhance collaboration among veterans, baby boomers, Generation X, Generation Y, and Fifth Generation employees continues to challenge organizational leaders. The purpose of this nonexperimental study was to identify how the implementation of information technology initiatives, coupled with the knowledge of learning styles, might enhance collaboration among generational cohort employees. The generational cohort theory, Maslow's hierarchy of needs theory, and the technology acceptance model were the theoretical frameworks used to develop an understanding of the relationships among the cohorts and the acceptance of technology to enhance collaboration. Data were collected from a …