Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Physical Sciences and Mathematics (8556)
- Computer Sciences (8539)
- Databases and Information Systems (3453)
- Software Engineering (2164)
- Artificial Intelligence and Robotics (1697)
-
- Information Security (1071)
- Numerical Analysis and Scientific Computing (1025)
- Graphics and Human Computer Interfaces (933)
- Engineering (888)
- Social and Behavioral Sciences (681)
- Business (642)
- Theory and Algorithms (493)
- Computer Engineering (451)
- Operations Research, Systems Engineering and Industrial Engineering (410)
- Programming Languages and Compilers (379)
- OS and Networks (324)
- Communication (297)
- Social Media (240)
- Public Affairs, Public Policy and Public Administration (217)
- Transportation (195)
- Medicine and Health Sciences (181)
- Education (170)
- Management Information Systems (167)
- Data Storage Systems (162)
- E-Commerce (148)
- International and Area Studies (111)
- Asian Studies (110)
- Health Information Technology (110)
- Digital Communications and Networking (104)
- Technology and Innovation (104)
- Keyword
-
- Deep learning (123)
- Machine learning (122)
- Social media (74)
- Artificial intelligence (72)
- Reinforcement learning (69)
-
- Privacy (65)
- Data mining (64)
- Cloud computing (58)
- Deep Learning (56)
- Empirical study (54)
- Optimization (54)
- Security (54)
- Visualization (51)
- Task analysis (50)
- Online learning (49)
- Software engineering (49)
- Training (49)
- Neural networks (48)
- Singapore (48)
- Anomaly detection (47)
- Feature extraction (46)
- Twitter (46)
- Large Language Models (45)
- Blockchain (44)
- Collaboration (44)
- Semantics (43)
- Access control (41)
- Algorithms (40)
- Android (39)
- Natural language processing (39)
- Publication Year
- File Type
Articles 6151 - 6180 of 8597
Full-Text Articles in Entire DC Network
Innovating Services In Science And Technology Parks, Arcot Desai Narasimhalu
Innovating Services In Science And Technology Parks, Arcot Desai Narasimhalu
Research Collection School Of Computing and Information Systems
Science and Technology Parks are in the business of providing services to their tenants, a mix of large companies, Small and Medium Enterprises and startups. The service needs of each of these types of companies will be different. The quality of services can be improved by understanding the needs of the tenants both, prior to building the Science and Technology Parks as well as on an ongoing basis. This paper introduces the CUGAR model for Science and Technology Parks as well as Service Innovation Design framework. It then proceeds to discuss how the Service Innovation framework could be applied to …
Theory And Practice, Do They Match? A Case With Spectrum-Based Fault Localization, Tien-Duy B. Le, Ferdian Thung, David Lo
Theory And Practice, Do They Match? A Case With Spectrum-Based Fault Localization, Tien-Duy B. Le, Ferdian Thung, David Lo
Research Collection School Of Computing and Information Systems
Spectrum-based fault localization refers to the process of identifying program units that are buggy from two sets of execution traces: normal traces and faulty traces. These approaches use statistical formulas to measure the suspiciousness of program units based on the execution traces. There have been many spectrum-based fault localization approaches proposing various formulas in the literature. Two of the best performing and well-known ones are Tarantula and Ochiai. Recently, Xie et al. find that theoretically, under certain assumptions, two families of spectrum-based fault localization formulas outperform all other formulas including those of Tarantula and Ochiai. In this work, we empirically …
The Impact Of Ineffective Internal Control On The Value Relevance Of Accounting Information, Nan Hu, Baolei Qi, Gaoliang Tian, Lee Yao, Zhen Zeng
The Impact Of Ineffective Internal Control On The Value Relevance Of Accounting Information, Nan Hu, Baolei Qi, Gaoliang Tian, Lee Yao, Zhen Zeng
Research Collection School Of Computing and Information Systems
This paper investigates the value relevance of accounting information in the presence of ineffective internal control (IIC). Based on Ohlson's valuation model, this paper first documents that IIC can directly affect a firm's market value after control cost of capital, corporate governance, and other, value-relevant variables. Second, this paper finds that the value relevance of earnings and book value in determining a firm's market value are significantly reduced. Collectively, the results of this paper indicate that the effectiveness of internal controls can directly affect a firm's market value and the value relevance of accounting information.
Generative Models For Item Adoptions Using Social Correlation, Freddy Chong Tat Chua, Hady Wirawan Lauw, Ee Peng Lim
Generative Models For Item Adoptions Using Social Correlation, Freddy Chong Tat Chua, Hady Wirawan Lauw, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Users face many choices on the Web when it comes to choosing which product to buy, which video to watch, etc. In making adoption decisions, users rely not only on their own preferences, but also on friends. We call the latter social correlation which may be caused by the homophily and social influence effects. In this paper, we focus on modeling social correlation on users’ item adoptions. Given a user-user social graph and an item-user adoption graph, our research seeks to answer the following questions: whether the items adopted by a user correlate to items adopted by her friends, and …
Web-Scale Near-Duplicate Search: Techniques And Applications, Chong-Wah Ngo, Changsheng Xu, Wessel Kraaij, Abdulmotaleb El Saddik
Web-Scale Near-Duplicate Search: Techniques And Applications, Chong-Wah Ngo, Changsheng Xu, Wessel Kraaij, Abdulmotaleb El Saddik
Research Collection School Of Computing and Information Systems
This paper presents some of the most recent advances in the research on Web-scale near-duplicate search and explores the potential for bringing this research a substantial step further. It contains high-quality contributions addressing various aspects of the Web-scale near-duplicate search problem in a number of relevant domains. The topics range from feature representation, matching, and indexing from different novel aspects to the adaptation of current technologies for mobile media search and photo archaeology mining.
A Highly Efficient Rfid Distance Bounding Protocol Without Real-Time Prf Evaluation, Yunhui Zhuang, Anjia Yang, Duncan S. Wong, Guomin Yang, Qi Xie
A Highly Efficient Rfid Distance Bounding Protocol Without Real-Time Prf Evaluation, Yunhui Zhuang, Anjia Yang, Duncan S. Wong, Guomin Yang, Qi Xie
Research Collection School Of Computing and Information Systems
There is a common situation among current distance bounding protocols in the literature: they set the fast bit exchange phase after a slow phase in which the nonces for both the reader and a tag are exchanged. The output computed in the slow phase is acting as the responses in the subsequent fast phase. Due to the calculation constrained RFID environment of being lightweight and efficient, it is the important objective of building the protocol which can have fewer number of message flows and less number of cryptographic operations in real time performed by the tag. In this paper, we …
Securearray: Improving Wifi Security With Fine-Grained Physical-Layer, Jie Xiong, Kyle Jamieson
Securearray: Improving Wifi Security With Fine-Grained Physical-Layer, Jie Xiong, Kyle Jamieson
Research Collection School Of Computing and Information Systems
Despite the important role that WiFi networks play in home and enterprise networks they are relatively weak from a security standpoint. With easily available directional antennas, attackers can be physically located off-site, yet compromise WiFi security protocols such as WEP, WPA, and even to some extent WPA2 through a range of exploits specific to those protocols, or simply by running dictionary and human-factors attacks on users' poorly-chosen passwords. This presents a security risk to the entire home or enterprise network. To mitigate this ongoing problem, we propose SecureArray, a system designed to operate alongside existing wireless security protocols, adding defense …
Focus: A Usable & Effective Approach To Oled Display Power Management, Kiat Wee Tan, Tadashi Okoshi, Archan Misra, Rajesh Krishna Balan
Focus: A Usable & Effective Approach To Oled Display Power Management, Kiat Wee Tan, Tadashi Okoshi, Archan Misra, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
In this paper, we present the design and implementation of Focus, a system for effectively and efficiently reducing power consumption of OLED displays on smartphones. These displays, while becoming exceedingly common still consume significant power. The key idea of Focus is that we use the notion of saliency to save display power by dimming portions of the applications that are less important to the user. We envision Focus being especially useful during low battery situations when usability is less important than power savings. We tested Focus using 15 applications running on a Samsung Galaxy S III and show that it …
Conferencesense: Monitoring Of Public Events Using Phone Sensors, Vigneshwaran Subbaraju, Amit Kumar, Vikrant Nandakumar, Sonali Batra, Salil Kanhere, Pradipta De, Vinayak Naik, Dipanjan Chakraborty, Archan Misra
Conferencesense: Monitoring Of Public Events Using Phone Sensors, Vigneshwaran Subbaraju, Amit Kumar, Vikrant Nandakumar, Sonali Batra, Salil Kanhere, Pradipta De, Vinayak Naik, Dipanjan Chakraborty, Archan Misra
Research Collection School Of Computing and Information Systems
We explore the use of a participatory sensing paradigm, where data generated from individual smartphones is used to extract and understand collective properties of temporary public gatherings and events (e.g., concerts & conferences). We focus on the use of this paradigm at a technical conference, and describe the design, implementation and deployment of ConferenceSense, an application that uses multiple sensor and human-generated inputs from attendees' smartphones to infer context, such as the start time of a session or the degree of interaction during a tea break. Based on data collected from multiple attendees at a 3-day conference, we explore how …
An Investigation Of Decision Analytic Methodologies For Stress Identification, Yong Deng, Chao-Hsien Chu, Huayou Si, Qixun Zhang, Zhonghai Wu
An Investigation Of Decision Analytic Methodologies For Stress Identification, Yong Deng, Chao-Hsien Chu, Huayou Si, Qixun Zhang, Zhonghai Wu
Research Collection School Of Computing and Information Systems
In modern society, more and more people are suffering from some type of stress. Monitoring and timely detecting of stress level will be very valuable for the person to take counter measures. In this paper, we investigate the use of decision analytics methodologies to detect stress. We present a new feature selection method based on the principal component analysis (PCA), compare three feature selection methods, and evaluate five information fusion methods for stress detection. A driving stress data set created by the MIT Media lab is used to evaluate the relative performance of these methods. Our study show that the …
Writing For Publication In Biomedical Informatics Journals, Christoph Lehmann, Reinhold Haux, Jan Talmon, Dominik Aronsky, Nicolette De Keizer, Tze-Yun Leong, Charles Safran
Writing For Publication In Biomedical Informatics Journals, Christoph Lehmann, Reinhold Haux, Jan Talmon, Dominik Aronsky, Nicolette De Keizer, Tze-Yun Leong, Charles Safran
Research Collection School Of Computing and Information Systems
No abstract provided.
An Empirical Study On Uncertainty Identification In Social Media Context, Zhongyu Wei, Junwen Chen, Wei Gao, Binyang Li, Lanjun Zhou, Yulan He, Kam-Fai Wong
An Empirical Study On Uncertainty Identification In Social Media Context, Zhongyu Wei, Junwen Chen, Wei Gao, Binyang Li, Lanjun Zhou, Yulan He, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Uncertainty text detection is important to many social-media-based applications since more and more users utilize social media platforms (e.g., Twitter, Facebook, etc.) as information source to produce or derive interpretations based on them. However, existing uncertainty cues are ineffective in social media context because of its specific characteristics. In this paper, we propose a variant of annotation scheme for uncertainty identification and construct the first uncertainty corpus based on tweets. We then conduct experiments on the generated tweets corpus to study the effectiveness of different types of features for uncertainty text identification.
Audit Games, Jeremiah Blocki, Nicolas Christin, Anupam Datta, Ariel D. Procaccia, Arunesh Sinha
Audit Games, Jeremiah Blocki, Nicolas Christin, Anupam Datta, Ariel D. Procaccia, Arunesh Sinha
Research Collection School Of Computing and Information Systems
Effective enforcement of laws and policies requires expending resources to prevent and detect offenders, as well as appropriate punishment schemes to deter violators. In particular, enforcement of privacy laws and policies in modern organizations that hold large volumes of personal information (e.g., hospitals, banks) relies heavily on internal audit mechanisms. We study economic considerations in the design of these mechanisms, focusing in particular on effective resource allocation and appropriate punishment schemes. We present an audit game model that is a natural generalization of a standard security game model for resource allocation with an additional punishment parameter. Computing the Stackelberg equilibrium …
Multi-View Discriminant Transfer Learning, Pei Yang Yang, Wei Gao
Multi-View Discriminant Transfer Learning, Pei Yang Yang, Wei Gao
Research Collection School Of Computing and Information Systems
We study to incorporate multiple views of data in a perceptive transfer learning framework and propose a Multi-view Discriminant Transfer (MDT) learning approach for domain adaptation. The main idea is to find the optimal discriminant weight vectors for each view such that the correlation between the two-view projected data is maximized, while both the domain discrepancy and the view disagreement are minimized simultaneously. Furthermore, we analyze MDT theoretically from discriminant analysis perspective to explain the condition and reason, under which the proposed method is not applicable. The analytical results allow us to investigate whether there exist within-view and/or betweenview conflicts, …
The User’S Communication Patterns On A Mobile Social Network Site, Youngsoo Kim
The User’S Communication Patterns On A Mobile Social Network Site, Youngsoo Kim
Research Collection School Of Computing and Information Systems
No abstract provided.
Usmmc: A Self-Contained Model Checker For Uml State Machines, Shuang Liu, Yang Liu, Jun Sun, Manchun Zheng, Bimlesh Wadhwa, Jin Song Dong
Usmmc: A Self-Contained Model Checker For Uml State Machines, Shuang Liu, Yang Liu, Jun Sun, Manchun Zheng, Bimlesh Wadhwa, Jin Song Dong
Research Collection School Of Computing and Information Systems
UML diagrams are gaining increasing usage in Object-Oriented system designs. UML state machines are specifically used in modeling dynamic behaviors of classes. It has been widely agreed that verification of system designs at an early stage will dramatically reduce the development cost. Tool support for verification UML designs can also encourage consistent usage of UML diagrams throughout the software development procedure. In this work, we present a tool, named USMMC, which turns model checking of UML state machines into practice. USMMC is a self-contained toolkit, which provides editing, interactive simulation as well as powerful model checking support for UML state …
An Empirical Analysis Of A Network Of Expertise, Le Truc Viet, Minh Thap Nguyen
An Empirical Analysis Of A Network Of Expertise, Le Truc Viet, Minh Thap Nguyen
Research Collection School Of Computing and Information Systems
In this paper, we analyze the network of expertise constructed from the interactions of users on the online questionanswering (QA) community of Stack Overflow. This community was built with the intention of helping users with their programming tasks and, thus, questions are expected to be highly factual. This also indicates that the answers one provides may be highly indicative of one's level of expertise on the subject matter. Therefore, our main concern is how to model and characterize the user's expertise based on the constructed network and its centrality measures. We used the user's reputation established on Stack Overflow as …
Learning To Name Faces: A Multimodal Learning Scheme For Search-Based Face Annotation, Dayong Wang, Steven C. H. Hoi, Pengcheng Wu, Jianke Zhu, Ying He, Chunyan Miao
Learning To Name Faces: A Multimodal Learning Scheme For Search-Based Face Annotation, Dayong Wang, Steven C. H. Hoi, Pengcheng Wu, Jianke Zhu, Ying He, Chunyan Miao
Research Collection School Of Computing and Information Systems
Automated face annotation aims to automatically detect human faces from a photo and further name the faces with the corresponding human names. In this paper, we tackle this open problem by investigating a search-based face annotation (SBFA) paradigm for mining large amounts of web facial images freely available on the WWW. Given a query facial image for annotation, the idea of SBFA is to first search for top-n similar facial images from a web facial image database and then exploit these top-ranked similar facial images and their weak labels for naming the query facial image. To fully mine those information, …
Improving Traffic Prediction With Tweet Semantics, Jingrui He, Wei Shen, Phani Divakaruni, Laura Wynter, Rick Lawrence
Improving Traffic Prediction With Tweet Semantics, Jingrui He, Wei Shen, Phani Divakaruni, Laura Wynter, Rick Lawrence
Research Collection School Of Computing and Information Systems
Road traffic prediction is a critical component in modern smart transportation systems. It provides the basis for traffic management agencies to generate proactive traffic operation strategies for alleviating congestion. Existing work on near-term traffic prediction (forecasting horizons in the range of 5 minutes to 1 hour) relies on the past and current traffic conditions. However, once the forecasting horizon is beyond 1 hour, i.e., in longer-term traffic prediction, these techniques do not work well since additional factors other than the past and current traffic conditions start to play important roles.To address this problem, in this paper, for the first time, …
Best Upgrade Plans For Large Road Networks, Yimin Lin, Kyriakos Mouratidis
Best Upgrade Plans For Large Road Networks, Yimin Lin, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
In this paper, we consider a new problem in the context of road network databases, named Resource Constrained Best Upgrade Plan computation (BUP, for short). Consider a transportation network (weighted graph) G where a subset of the edges are upgradable, i.e., for each such edge there is a cost, which if spent, the weight of the edge can be reduced to a specific new value. Given a source and a destination in G, and a budget (resource constraint) B, the BUP problem is to identify which upgradable edges should be upgraded so that the shortest path distance between source and …
Flotra: Flower-Shape Trajectory Mining For Instance-Specific Parameter Tuning, Lindawati Lindawati, Feida Zhu, Hoong Chuin Lau
Flotra: Flower-Shape Trajectory Mining For Instance-Specific Parameter Tuning, Lindawati Lindawati, Feida Zhu, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
The performance of a heuristic algorithm is highly dependent on its parameter configuration, yet finding a good parameter configuration is often a time-consuming task. In this paper we propose FloTra, a Flower graph mining for graph search Trajectory pattern extraction for generic instance-specific automated parameter tuning. This algorithm provides efficient extraction of compact and discriminative features of the search trajectory, upon which problem instances are clustered and the corresponding optimal parameter configurations are computed. Experimental evaluations of our approach on the Quadratic Assignment Problem (QAP) show that our approach offers promising improvement over existing parameter tuning algorithms. In this work, …
“Network-Theoretic” Queuing Delay Estimation In Theme Park Attractions, Ajay Aravamudhan, Archan Misra, Hoong Chuin Lau
“Network-Theoretic” Queuing Delay Estimation In Theme Park Attractions, Ajay Aravamudhan, Archan Misra, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Queuing is a common phenomenon in theme parks which negatively affects visitor experience and revenue yields. There is thus a need for park operators to infer the real queuing delays without expensive investment in human effort or complex tracking infrastructure. In this paper, we depart from the classical queuing theory approach and provide a data-driven and online approach for estimating the time-varying queuing delays experienced at different attractions in a theme park. This work is novel in that it relies purely on empirical observations of the entry time of individual visitors at different attractions, and also accommodates the reality that …
A Multi-Objective Memetic Algorithm For Vehicle Resource Allocation In Sustainable Transportation Planning, Hoong Chuin Lau, Lucas Agussurja, Shih-Fen Cheng, Pang Jin Tan
A Multi-Objective Memetic Algorithm For Vehicle Resource Allocation In Sustainable Transportation Planning, Hoong Chuin Lau, Lucas Agussurja, Shih-Fen Cheng, Pang Jin Tan
Research Collection School Of Computing and Information Systems
Sustainable supply chain management has been an increasingly important topic of research in recent years. At the strategic level, there are computational models which study supply and distribution networks with environmental considerations. At the operational level, there are, for example, routing and scheduling models which are constrained by carbon emissions. Our paper explores work in tactical planning with regards to vehicle resource allocation from distribution centers to customer locations in a multi-echelon logistics network. We formulate the bi-objective optimization problem exactly and design a memetic algorithm to efficiently derive an approximate Pareto front. We illustrate the applicability of our approach …
Interacting Knapsack Problem In Designing Resource Bundles, Truong Huy D. Nguyen, Pradeep Reddy Varakantham, Hoong Chuin Lau, Shih-Fen Cheng
Interacting Knapsack Problem In Designing Resource Bundles, Truong Huy D. Nguyen, Pradeep Reddy Varakantham, Hoong Chuin Lau, Shih-Fen Cheng
Research Collection School Of Computing and Information Systems
In many real-life businesses, the service provider/seller keeps a log of the visitors’ behavior as a way to assess the efficiency of the current business/operation model and find room for improvement. For example, by tracking when visitors entering attractions in a theme park, theme park owners can detect when and where congestion may occur, thus having contingency plans to reroute the visitors accordingly. Similarly, a Cable TV service provider can track channel switching events at each household to identify uninteresting channels. Subsequently, the repertoire of channels up for subscription can evolve over time to better serve the entertainment demand of …
Attribute-Based Encryption With Verifiable Outsourced Decryption, Junzuo Lai, Robert H. Deng, Chaowen Guan, Jian Weng
Attribute-Based Encryption With Verifiable Outsourced Decryption, Junzuo Lai, Robert H. Deng, Chaowen Guan, Jian Weng
Research Collection School Of Computing and Information Systems
Attribute-based encryption (ABE) is a public-keybased one-to-many encryption that allows users to encrypt and decrypt data based on user attributes. A promising application of ABE is flexible access control of encrypted data stored in the cloud, using access polices and ascribed attributes associated with private keys and ciphertexts.One of themain efficiency drawbacks of the existing ABE schemes is that decryption involves expensive pairing operations and the number of such operations grows with the complexity of the access policy. Recently, Green et al. proposed an ABE system with outsourced decryption that largely eliminates the decryption overhead for users. In such a …
Delayflow Centrality For Identifying Critical Nodes In Transportation Networks, Yew-Yih Cheng, Roy Ka Wei Lee, Ee-Peng Lim, Feida Zhu
Delayflow Centrality For Identifying Critical Nodes In Transportation Networks, Yew-Yih Cheng, Roy Ka Wei Lee, Ee-Peng Lim, Feida Zhu
Research Collection School Of Computing and Information Systems
In an urban city, its transportation network supports efficient flow of people between different parts of the city. Failures in the network can cause major disruptions to commuter and business activities which can result in both significant economic and time losses. In this paper, we investigate the use of centrality measures to determine critical nodes in a transportation network so as to improve the design of the network as well as to devise plans for coping with network failures. Most centrality measures in social network analysis research unfortunately consider only topological structure of the network and are oblivious of transportation …
Incremental And Accuracy-Aware Personalized Pagerank Through Scheduled Approximation, Fanwei Zhu, Yuan Fang, Kevin Chen-Chuan Chang, Jing Ying
Incremental And Accuracy-Aware Personalized Pagerank Through Scheduled Approximation, Fanwei Zhu, Yuan Fang, Kevin Chen-Chuan Chang, Jing Ying
Research Collection School Of Computing and Information Systems
As Personalized PageRank has been widely leveraged for ranking on a graph, the efficient computation of Personalized PageRank Vector (PPV) becomes a prominent issue. In this paper, we propose FastPPV, an approximate PPV computation algorithm that is incremental and accuracy-aware. Our approach hinges on a novel paradigm of scheduled approximation: the computation is partitioned and scheduled for processing in an "organized" way, such that we can gradually improve our PPV estimation in an incremental manner, and quantify the accuracy of our approximation at query time. Guided by this principle, we develop an efficient hub based realization, where we adopt the …
Vigilance Adaptation In Adaptive Resonance Theory, Lei Meng, Ah-Hwee Tan, Donald C. Winsch
Vigilance Adaptation In Adaptive Resonance Theory, Lei Meng, Ah-Hwee Tan, Donald C. Winsch
Research Collection School Of Computing and Information Systems
Despite the advantages of fast and stable learning, Adaptive Resonance Theory (ART) still relies on an empirically fixed vigilance parameter value to determine the vigilance regions of all of the clusters in the category field (F 2 ), causing its performance to depend on the vigilance value. It would be desirable to use different values of vigilance for different category field nodes, in order to fit the data with a smaller number of categories. We therefore introduce two methods, the Activation Maximization Rule (AMR) and the Confliction Minimization Rule (CMR). Despite their differences, both ART with AMR (AM-ART) and with …
An Agent-Based Network Analytic Perspective On The Evolution Of Complex Adaptive Supply Chain Networks, L. Ponnambalam, A. Tan, X. Fu, X. F. Yin, Zhaoxia Wang, R. S. Goh
An Agent-Based Network Analytic Perspective On The Evolution Of Complex Adaptive Supply Chain Networks, L. Ponnambalam, A. Tan, X. Fu, X. F. Yin, Zhaoxia Wang, R. S. Goh
Research Collection School Of Computing and Information Systems
Supply chain networks of modern era are complex adaptive systems that are dynamic and highly interdependent in nature. Business continuity of these complex systems depend vastly on understanding as to how the supply chain network evolves over time (based on the policies it adapts), and identifying the susceptibility of the evolved networks to external disruptions. The objective of this article is to illustrate as to how an agent-based network analytic perspective can aid this understanding on the network-evolution dynamics, and identification of disruption effects on the evolved networks. To this end, we developed a 4-tier agent based supply chain model …
Cost-Sensitive Online Active Learning With Application To Malicious Url Detection, Peilin Zhao, Steven C. H. Hoi
Cost-Sensitive Online Active Learning With Application To Malicious Url Detection, Peilin Zhao, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Malicious Uniform Resource Locator (URL) detection is an important problem in web search and mining, which plays a critical role in internet security. In literature, many existing studies have attempted to formulate the problem as a regular supervised binary classification task, which typically aims to optimize the prediction accuracy. However, in a real-world malicious URL detection task, the ratio between the number of malicious URLs and legitimate URLs is highly imbalanced, making it very inappropriate for simply optimizing the prediction accuracy. Besides, another key limitation of the existing work is to assume a large amount of training data is available, …