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Full-Text Articles in Entire DC Network
Semi-Autonomous Virtual Valet Parking, Arne Suppe, Luis Navarro-Serment, Aaron Steinfeld
Semi-Autonomous Virtual Valet Parking, Arne Suppe, Luis Navarro-Serment, Aaron Steinfeld
Research Collection School Of Computing and Information Systems
Despite regulations specifying parking spots that support wheelchair vans, it is not uncommon for end users to encounter problems with clearance for van ramps. Even if a driver elects to park in the far reaches of a parking lot as a precautionary measure, there is no guarantee that the spot next to their van will be empty when they return. Likewise, the prevalence of older drivers who experience significant difficulty with ingress and egress from vehicles is nontrivial and the ability to fully open a car door is important. This work describes a method and user interaction for low cost, …
Vireo At Trecvid 2010: Semantic Indexing, Known-Item Search, And Content-Based Copy Detection, Chong-Wah Ngo, Shi-Ai Zhu, Hung-Khoon Tan, Wan-Lei Zhao
Vireo At Trecvid 2010: Semantic Indexing, Known-Item Search, And Content-Based Copy Detection, Chong-Wah Ngo, Shi-Ai Zhu, Hung-Khoon Tan, Wan-Lei Zhao
Research Collection School Of Computing and Information Systems
This paper presents our approaches and the comparative analysis of our results for the three TRECVID 2010 tasks that we participated in: semantic indexing, known-item search and content-based copy detection.
Revenue Management Model For On-Demand It Services, Tieming Liu, Chinnatat Methapatara, Laura Wynter
Revenue Management Model For On-Demand It Services, Tieming Liu, Chinnatat Methapatara, Laura Wynter
Research Collection School Of Computing and Information Systems
This paper presents a model for applying revenue management to on-demand IT services. The multinomial logit model is used to describe customer choice over multiple classes with different service-level agreements (SLAs). A nonlinear programming model is provided to determine the optimal price or service level for each class. Through a numerical analysis, we examine the impacts of system capacity and customer waiting incentives on the service provider’s profit and pricing strategies.
Model Checking Hierarchical Probabilistic Systems, Jun Sun, Songzheng Song, Yang Liu
Model Checking Hierarchical Probabilistic Systems, Jun Sun, Songzheng Song, Yang Liu
Research Collection School Of Computing and Information Systems
Probabilistic modeling is important for random distributed algorithms, bio-systems or decision processes. Probabilistic model checking is a systematic way of analyzing finite-state probabilistic models. Existing probabilistic model checkers have been designed for simple systems without hierarchy. In this paper, we extend the PAT toolkit to support probabilistic model checking of hierarchical complex systems. We propose to use PCSP#, a combination of Hoare’s CSP with data and probability, to model such systems. In addition to temporal logic, we allow complex safety properties to be specified by non-probabilistic PCSP# model. Validity of the properties (with probability) is established by refinement checking. Furthermore, …
Evolution Of A Bluetooth Test Application Product Line: A Case Study, Narayanasamy Ramasubbu, Rajesh Krishna Balan
Evolution Of A Bluetooth Test Application Product Line: A Case Study, Narayanasamy Ramasubbu, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
In this paper, we study the decision making process involved in the five year lifecycle of a Bluetooth software product produced by a large, multi-national test and measurement firm. In this environment, customer change requests either have to be added as a standard feature in the product, or developed as a special customized version of the product. We first discuss the influential factors, such as evolving standards, market share, installed-base, and complexity, which collectively determined how the firm responded to product change requests. We then develop a predictive decision model to test the collective impact of these factors on determining …
Online Multiple Kernel Learning: Algorithms And Mistake Bounds, Rong Jin, Steven C. H. Hoi, Tianbao Yang
Online Multiple Kernel Learning: Algorithms And Mistake Bounds, Rong Jin, Steven C. H. Hoi, Tianbao Yang
Research Collection School Of Computing and Information Systems
Online learning and kernel learning are two active research topics in machine learning. Although each of them has been studied extensively, there is a limited effort in addressing the intersecting research. In this paper, we introduce a new research problem, termed Online Multiple Kernel Learning (OMKL), that aims to learn a kernel based prediction function from a pool of predefined kernels in an online learning fashion. OMKL is generally more challenging than typical online learning because both the kernel classifiers and their linear combination weights must be learned simultaneously. In this work, we consider two setups for OMKL, i.e. combining …
Data-Driven Approaches To Community-Contributed Video Applications, Xiao Wu, Chong-Wah Ngo, Wan-Lei Zhao
Data-Driven Approaches To Community-Contributed Video Applications, Xiao Wu, Chong-Wah Ngo, Wan-Lei Zhao
Research Collection School Of Computing and Information Systems
With the prosperity of video-sharing websites such as YouTube, the amount of community-contributed video has increased dramatically. Reportedly more than 65,000 new videos were uploaded to YouTube every day in July 2006 and it's estimated that 20 hours of new videos were uploaded to the site every minute in May 2009. In addition to the huge volume of video data, the social Web provides rich contextual and social resources associated with videos. These resources include title, tags, thumbnails, related videos, and user and community information, as illustrated in Figure 1. While billions of user-generated videos accompanied with rich-media information have …
Youth Olympic Village Co-Space, Zin-Yan Chua, Yilin Kang, Xing Jiang, Kah-Hoe Pang, Andrew C. Gregory, Chi-Yun Tan, Wai-Lun Wong, Ah-Hwee Tan, Yew-Soon Ong, Chunyan Miao
Youth Olympic Village Co-Space, Zin-Yan Chua, Yilin Kang, Xing Jiang, Kah-Hoe Pang, Andrew C. Gregory, Chi-Yun Tan, Wai-Lun Wong, Ah-Hwee Tan, Yew-Soon Ong, Chunyan Miao
Research Collection School Of Computing and Information Systems
We have designed and implemented a 3D virtual world based on the Co-Space concept encompasses the Youth Olympic Village (YOV) and several sports competition venues. It is a massively multiplayer online (MMO) virtual world built according to the actual, physical locations of the YOV and sports competition venues. On top of that, the Co-Space is being populated with human-like avatars, which are created according to the actual human size and appearance; they perform their activities and interact with the users in realworld context. In addition, autonomous intelligent agents are integrated into the Co-Space to provide context-aware and personalized services to …
Wireless Sensing Without Sensors: An Experimental Study Of Motion/Intrusion Detection Using Rf Irregularity, Wei Qi Lee, Winston K. G. Seah, Hwee-Pink Tan, Zexi Yao
Wireless Sensing Without Sensors: An Experimental Study Of Motion/Intrusion Detection Using Rf Irregularity, Wei Qi Lee, Winston K. G. Seah, Hwee-Pink Tan, Zexi Yao
Research Collection School Of Computing and Information Systems
Motion and intrusion detection are often cited as wireless sensor network (WSN) applications with typical configurations comprising clusters of wireless nodes equipped with motion sensors to detect human motion. Currently, WSN performance is subjected to several constraints, namely radio irregularity and finite on-board computation/energy resources. Radio irregularity in radio frequency (RF) propagation rises to a higher level in the presence of human activity due to the absorption effect of the human body. In this paper, we investigate the feasibility of monitoring RF transmission for the purpose of intrusion detection through experimentation. With empirical data obtained from the Crossbow TelosB platform …
Mining Collaboration Patterns From A Large Developer Network, Didi Surian, David Lo, Ee Peng Lim
Mining Collaboration Patterns From A Large Developer Network, Didi Surian, David Lo, Ee Peng Lim
Research Collection School Of Computing and Information Systems
In this study, we extract patterns from a large developer collaborations network extracted from Source Forge. Net at high and low level of details. At the high level of details, we extract various network-level statistics from the network. At the low level of details, we extract topological sub-graph patterns that are frequently seen among collaborating developers. Extracting sub graph patterns from large graphs is a hard NP-complete problem. To address this challenge, we employ a novel combination of graph mining and graph matching by leveraging network-level properties of a developer network. With the approach, we successfully analyze a snapshot of …
Co-Creation And Collaboration In A Virtual World: A 3d Visualization Design Project In Second Life, Keng Siau, Fiona Fui-Hoon Nah, B. Mennecke, S. Schiller
Co-Creation And Collaboration In A Virtual World: A 3d Visualization Design Project In Second Life, Keng Siau, Fiona Fui-Hoon Nah, B. Mennecke, S. Schiller
Research Collection School Of Computing and Information Systems
One of the most successful and useful implementations of 3D virtual worlds is in the area of education and training. This paper discusses the use of virtual worlds in education and describes an innovative 3D visualization design project using one of the most popular virtual worlds, Second Life. This ongoing project is a partnership between IBM and three universities in the United States: the University of Nebraska-Lincoln, Iowa State University, and Wright State University. More than 400 MBA students have participated in this project by completing a creative design project that involves co-creation and collaboration in Second Life. The MBA …
Mining Interesting Link Formation Rules In Social Networks, Cane Wing-Ki Leung, Ee Peng Lim, David Lo, Jianshu Weng
Mining Interesting Link Formation Rules In Social Networks, Cane Wing-Ki Leung, Ee Peng Lim, David Lo, Jianshu Weng
Research Collection School Of Computing and Information Systems
Link structures are important patterns one looks out for when modeling and analyzing social networks. In this paper, we propose the task of mining interesting Link Formation rules (LF-rules) containing link structures known as Link Formation patterns (LF-patterns). LF-patterns capture various dyadic and/or triadic structures among groups of nodes, while LF-rules capture the formation of a new link from a focal node to another node as a postcondition of existing connections between the two nodes. We devise a novel LF-rule mining algorithm, known as LFR-Miner, based on frequent subgraph mining for our task. In addition to using a support-confidence framework …
Cast2face: Character Identification In Movie With Actor-Character Correspondence, Mengdi Xu, Xiaotong Yuan, Jialie Shen, Shuicheng Yan
Cast2face: Character Identification In Movie With Actor-Character Correspondence, Mengdi Xu, Xiaotong Yuan, Jialie Shen, Shuicheng Yan
Research Collection School Of Computing and Information Systems
We investigate the problem of automatically identifying characters in a movie with the supervision of actor-character name correspondence provided by the movie cast. Our proposed framework, namely Cast2Face, is featured by: (i) we restrict the names to assign within the set of character names in the cast; (ii) for each character, by using the corresponding actor's name as a key word, we retrieve from Google image search a group of face images to form the gallery set; and (iii) the probe face tracks in the movie are then identified as one of the actors by robust multi-task joint sparse representation …
Attracting The Community's Many Eyes: An Exploration Of User Involvement In Issue Tracking, Lars Grammel, Holger Schackmann, Adrian Schröter, Christoph Treude, Margaret-Anne Storey
Attracting The Community's Many Eyes: An Exploration Of User Involvement In Issue Tracking, Lars Grammel, Holger Schackmann, Adrian Schröter, Christoph Treude, Margaret-Anne Storey
Research Collection School Of Computing and Information Systems
A community of users who report bugs and request features provides valuable feedback that can be used in product development. We compare the community involvement in issue tracker usage between the open source project Eclipse and the closed source project IBM Jazz to evaluate if publicly accessible issue trackers work as well in closed source projects. We find that IBM Jazz successfully receives user feedback through this channel. We then explore the differences in work item processing in IBM Jazz between team members, project members and externals. We conclude that making public issue trackers available in closed source projects is …
Rich Internet Geoweb For Spatial Data Infrastructure, Tin Seong Kam
Rich Internet Geoweb For Spatial Data Infrastructure, Tin Seong Kam
Research Collection School Of Computing and Information Systems
In this information age, more and more public statistical data such as population census, household living, local economy and business establishment are distributed over the internet within the framework of spatial data infrastructure. By and large, these data are organized geographically such as region, province as well as district. Usually, they are published in the form of digital maps over the internet as simple points, lines and polygons markers limited or no analytical function available to transform these data into useful information. To meet the analytical needs of casual public data users, we contribute RIGVAT, a rich internet geospatial visual …
Wsm'10: Second Acm Workshop On Social Media, Susanne Boll, Steven C. H. Hoi, Roelof Van Zwol, Jiebo Luo
Wsm'10: Second Acm Workshop On Social Media, Susanne Boll, Steven C. H. Hoi, Roelof Van Zwol, Jiebo Luo
Research Collection School Of Computing and Information Systems
The ACM SIGMM International Workshop on Social Media (WSM'10) is the second workshop held in conjunction with the ACM International Multimedia Conference (MM'10) at Firenze, Italy, 2010. This workshop provides a forum for researchers and practitioners from all over the world to share information on their latest investigations on social media analysis, exploration, search, mining, and emerging new social media applications.
Secureangle: Improving Wireless Security Using Angle-Of-Arrival Information, Jie Xiong, Kyle Jamieson
Secureangle: Improving Wireless Security Using Angle-Of-Arrival Information, Jie Xiong, Kyle Jamieson
Research Collection School Of Computing and Information Systems
Wireless networks play an important role in our everyday lives, at the workplace and at home. However, they are also relatively vulnerable: physically located off site, attackers can circumvent wireless security protocols such as WEP, WPA, and even to some extent WPA2, presenting a security risk to the entire network. To address this problem, we propose SecureAngle, a system designed to operate alongside existing wireless security protocols, adding defense in depth. SecureAngle leverages multi-antenna APs to profile the directions at which a client's signal arrives, using this angle-of-arrival (AoA) information to construct signatures that uniquely identify each client. We identify …
Finding Unusual Review Patterns Using Unexpected Rules, Nitin Jindal, Bing Liu, Ee Peng Lim
Finding Unusual Review Patterns Using Unexpected Rules, Nitin Jindal, Bing Liu, Ee Peng Lim
Research Collection School Of Computing and Information Systems
In recent years, opinion mining attracted a great deal of research attention. However, limited work has been done on detecting opinion spam (or fake reviews). The problem is analogous to spam in Web search [1, 9 11]. However, review spam is harder to detect because it is very hard, if not impossible, to recognize fake reviews by manually reading them [2]. This paper deals with a restricted problem, i.e., identifying unusual review patterns which can represent suspicious behaviors of reviewers. We formulate the problem as finding unexpected rules. The technique is domain independent. Using the technique, we analyzed an Amazon.com …
Trajectory-Based Visualization Of Web Video Topics, Juan Cao, Chong-Wah Ngo, Yong-Dong Zhang, Dong-Ming Zhang, Liang Ma
Trajectory-Based Visualization Of Web Video Topics, Juan Cao, Chong-Wah Ngo, Yong-Dong Zhang, Dong-Ming Zhang, Liang Ma
Research Collection School Of Computing and Information Systems
While there have been research efforts in organizing largescale web videos into topics, efficient browsing of web video topics remains a challenging problem not yet addressed. The related issues include how to efficiently browse and track the evolution of topics and eventually locate the videos of interest. In this paper, we introduce a novel interface for visualizing video topics as evolution trajectories. The trajectory visualization is capable of highlighting milestone events and depicting the topical hotness over time. The interface also allows multi-level browsing from topics to events and to videos, resulting in search exploration could be more efficiently conducted …
Business Network-Based Value Creation In Electronic Commerce, Robert John Kauffman, Ting Li, Eric Van Heck
Business Network-Based Value Creation In Electronic Commerce, Robert John Kauffman, Ting Li, Eric Van Heck
Research Collection School Of Computing and Information Systems
Information technologies (IT) have affected economic activities within and beyond the boundaries of the firm, changing the face of e-commerce. This article explores the circumstances under which value is created in business networks made possible by IT. Business networks combine the capabilities of multiple firms to produce and deliver products and services that none of them could more economically produce on its own and for which there is demand in the market. We call this business network-based value creation. We apply economic theory to explain the conditions under which business networks will exist and are able to sustain their value-producing …
Effects Of National Culture On Types Of Knowledge Sharing In Virtual Communities, Keng Siau, J. Erickson, Fiona Fui-Hoon Nah
Effects Of National Culture On Types Of Knowledge Sharing In Virtual Communities, Keng Siau, J. Erickson, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Organizations are using virtual communities to facilitate knowledge management and to enhance communication among employees, customers, and other interested individuals. Individual users can use virtual communities to engage in knowledge sharing. Professional communicators need to understand and adapt to a globalized and “flat” world, where people across different cultures interact freely and easily with one another in virtual communities. An intriguing question regarding virtual communities relates to whether national culture affects communication and types of knowledge sharing. This study examines the influence of US and Chinese national cultures on types of knowledge-sharing activities in virtual communities. The findings indicate that …
Context Modeling For Ranking And Tagging Bursty Features In Text Streams, Xin Zhao, Jing Jiang, Jing He, Xiaoming Li, Hongfei Yan, Dongdong Shan
Context Modeling For Ranking And Tagging Bursty Features In Text Streams, Xin Zhao, Jing Jiang, Jing He, Xiaoming Li, Hongfei Yan, Dongdong Shan
Research Collection School Of Computing and Information Systems
Bursty features in text streams are very useful in many text mining applications. Most existing studies detect bursty features based purely on term frequency changes without taking into account the semantic contexts of terms, and as a result the detected bursty features may not always be interesting or easy to interpret. In this paper we propose to model the contexts of bursty features using a language modeling approach. We then propose a novel topic diversity-based metric using the context models to find newsworthy bursty features. We also propose to use the context models to automatically assign meaningful tags to bursty …
Detecting Product Review Spammers Using Rating Behaviors, Ee Peng Lim, Viet-An Nguyen, Nitin Jindal, Bing Liu, Hady Wirawan Lauw
Detecting Product Review Spammers Using Rating Behaviors, Ee Peng Lim, Viet-An Nguyen, Nitin Jindal, Bing Liu, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
This paper aims to detect users generating spam reviews or review spammers. We identify several characteristic be- haviors of review spammers and model these behaviors so as to detect the spammers. In particular, we seek to model the following behaviors. First, spammers may target specific products or product groups in order to maximize their im- pact. Second, they tend to deviate from the other reviewers in their ratings of products. We propose scoring methods to measure the degree of spam for each reviewer and apply them on an Amazon review dataset. We then select a sub- set of highly suspicious …
Jointly Modeling Aspects And Opinions With A Maxent-Lda Hybrid, Xin Zhao, Jing Jiang, Hongfei Yan, Xiaoming Li
Jointly Modeling Aspects And Opinions With A Maxent-Lda Hybrid, Xin Zhao, Jing Jiang, Hongfei Yan, Xiaoming Li
Research Collection School Of Computing and Information Systems
Discovering and summarizing opinions from online reviews is an important and challenging task. A commonly-adopted framework generates structured review summaries with aspects and opinions. Recently topic models have been used to identify meaningful review aspects, but existing topic models do not identify aspect-specific opinion words. In this paper, we propose a MaxEnt-LDA hybrid model to jointly discover both aspects and aspect-specific opinion words. We show that with a relatively small amount of training data, our model can effectively identify aspect and opinion words simultaneously. We also demonstrate the domain adaptability of our model.
Modeling 3d Facial Expressions Using Geometry Videos, Jiazhi Xia, Ying He, Dao T. P. Quynh, Xiaoming Chen, Steven C. H. Hoi
Modeling 3d Facial Expressions Using Geometry Videos, Jiazhi Xia, Ying He, Dao T. P. Quynh, Xiaoming Chen, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
The significant advances in developing high-speed shape acquisition devices make it possible to capture the moving and deforming objects at video speeds. However, due to its complicated nature, it is technically challenging to effectively model and store the captured motion data. In this paper, we present a set of algorithms to construct geometry videos for 3D facial expressions, including hole filling, geodesic-based face segmentation, and expression-invariant parametrization. Our algorithms are efficient and robust, and can guarantee the exact correspondence of the salient features (eyes, mouth and nose). Geometry video naturally bridges the 3D motion data and 2D video, and provides …
Secureangle: Improving Wireless Security Using Angle-Of-Arrival Information, Jie Xiong, Kyle Jamieson
Secureangle: Improving Wireless Security Using Angle-Of-Arrival Information, Jie Xiong, Kyle Jamieson
Research Collection School Of Computing and Information Systems
Wireless networks play an important role in our everyday lives, at the workplace and at home. However, they are also relatively vulnerable: physically located off site, attackers can circumvent wireless security protocols such as WEP, WPA, and even to some extent WPA2, presenting a security risk to the entire network. To address this problem, we propose SecureAngle, a system designed to operate alongside existing wireless security protocols, adding defense in depth. SecureAngle leverages multi-antenna APs to profile the directions at which a client's signal arrives, using this angle-of-arrival (AoA) information to construct signatures that uniquely identify each client. We identify …
A Biologically-Inspired Cognitive Agent Model Integrating Declarative Knowledge And Reinforcement Learning, Ah-Hwee Tan, Gee-Wah Ng
A Biologically-Inspired Cognitive Agent Model Integrating Declarative Knowledge And Reinforcement Learning, Ah-Hwee Tan, Gee-Wah Ng
Research Collection School Of Computing and Information Systems
The paper proposes a biologically-inspired cognitive agent model, known as FALCON-X, based on an integration of the Adaptive Control of Thought (ACT-R) architecture and a class of self-organizing neural networks called fusion Adaptive Resonance Theory (fusion ART). By replacing the production system of ACT-R by a fusion ART model, FALCON-X integrates high-level deliberative cognitive behaviors and real-time learning abilities, based on biologically plausible neural pathways. We illustrate how FALCON-X, consisting of a core inference area interacting with the associated intentional, declarative, perceptual, motor and critic memory modules, can be used to build virtual robots for battles in a simulated RoboCode …
Scenario-Based And Value-Based Specification Mining: Better Together, David Lo, Shahar Maoz
Scenario-Based And Value-Based Specification Mining: Better Together, David Lo, Shahar Maoz
Research Collection School Of Computing and Information Systems
Specification mining takes execution traces as input and extracts likely program invariants, which can be used for comprehension, verification, and evolution related tasks. In this work we integrate scenario-based specification mining, which uses data-mining algorithms to suggest ordering constraints in the form of live sequence charts, an inter-object, visual, modal, scenario-based specification language, with mining of value-based invariants, which detects likely invariants holding at specific program points. The key to the integration is a technique we call scenario-based slicing, running on top of the mining algorithms to distinguish the scenario-specific invariants from the general ones. The resulting suggested specifications are …
Matching Dependence-Related Queries In The System Dependence Graph., Xiaoyin Wang, David Lo, Jiefeng Cheng, Lu Zhang, Hong Mei, Jeffrey Xu Yu
Matching Dependence-Related Queries In The System Dependence Graph., Xiaoyin Wang, David Lo, Jiefeng Cheng, Lu Zhang, Hong Mei, Jeffrey Xu Yu
Research Collection School Of Computing and Information Systems
In software maintenance and evolution, it is common that developers want to apply a change to a number of similar places. Due to the size and complexity of the code base, it is challenging for developers to locate all the places that need the change. A main challenge in locating the places that need the change is that, these places share certain common dependence conditions but existing code searching techniques can hardly handle dependence relations satisfactorily. In this paper, we propose a technique that enables developers to make queries involving dependence conditions and textual conditions on the system dependence graph …
Shortest Path Computation On Air Indexes, Georgios Kellaris, Kyriakos Mouratidis
Shortest Path Computation On Air Indexes, Georgios Kellaris, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
Shortest path computation is one of the most common queries in location-based services that involve transportation net- works. Motivated by scalability challenges faced in the mo- bile network industry, we propose adopting the wireless broad- cast model for such location-dependent applications. In this model the data are continuously transmitted on the air, while clients listen to the broadcast and process their queries locally. Although spatial problems have been considered in this environment, there exists no study on shortest path queries in road networks. We develop the rst framework to compute shortest paths on the air, and demonstrate the practicality and …