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Articles 7291 - 7320 of 9003
Full-Text Articles in Computer Sciences
Modeling Link Formation Behaviors In Dynamic Social Networks, Viet-An Nguyen, Cane Wing-Ki Leung, Ee Peng Lim
Modeling Link Formation Behaviors In Dynamic Social Networks, Viet-An Nguyen, Cane Wing-Ki Leung, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Online social networks are dynamic in nature. While links between users are seemingly formed and removed randomly, there exists some interested link formation behaviors demonstrated by users performing link creation and removal activities. Uncovering these behaviors not only allows us to gain deep insights of the users, but also pave the way to decipher how social links are formed. In this paper, we propose a general framework to define user link formation behaviors using well studied local link structures (i.e., triads and dyads) in a dynamic social network where links are formed at different timestamps. Depending on the role a …
An Energy Efficient Quality Adaptive Multi-Modal Sensor Framework For Context Recognition, Nirmalya Roy, Archan Misra, Christine Julien, Sajal K. Das, Jit Biswas
An Energy Efficient Quality Adaptive Multi-Modal Sensor Framework For Context Recognition, Nirmalya Roy, Archan Misra, Christine Julien, Sajal K. Das, Jit Biswas
Research Collection School Of Computing and Information Systems
Proliferation of mobile applications in unpredictable and changing environments requires applications to sense and act on changing operational contexts. In such environments, understanding the context of an entity is essential for adaptability of the application behavior to changing situations. In our view, context is a high-level representation of a user or entity’s state and can capture activities, relationships, capabilities, etc. Inherently, however, these high-level context measures are difficult to sense directly and instead must be inferred through the combination of many data sources. In pervasive computing environments where this context is of significant importance, a multitude of sensors is already …
A Virtualization-Based Approach For Zone Migration In Distributed Virtual Environments, Nguyen Binh Duong Ta, Thang Nguyen, Tran Nguyen, Do Nguyen, Xueyan Tang, Wentong Cai, Suiping Zhou
A Virtualization-Based Approach For Zone Migration In Distributed Virtual Environments, Nguyen Binh Duong Ta, Thang Nguyen, Tran Nguyen, Do Nguyen, Xueyan Tang, Wentong Cai, Suiping Zhou
Research Collection School Of Computing and Information Systems
This paper deals with the zone migration problem in large-scale distributed virtual environments (DVEs), e.g., massively multi-player online games, distributed military simulations, etc. To support real-time interactions among thousands of concurrent, geographically separated clients, a distributed server architecture is generally needed. In such architecture, the large virtual world can be partitioned into multiple smaller zones, enabling load distributions or zone-to-server mappings to improve interactivity. For example, a zone might be mapped (assigned) to a server location near most of its clients to reduce network latency. In this paper, we consider the problem of live zone migration over wide area networks …
How Information Management Capability Influences Firm Performance, Sunil Mithas, Narayan Ramasubbu, V. Sambamurthy
How Information Management Capability Influences Firm Performance, Sunil Mithas, Narayan Ramasubbu, V. Sambamurthy
Research Collection School Of Computing and Information Systems
How do information technology capabilities contribute to firm performance? This study develops a conceptual model linking IT-enabled information management capability with three important organizational capabilities (customer management capability, process management capability, and performance management capability). We argue that these three capabilities mediate the relationship between information management capability and firm performance. To test our conceptual model, we use a rare archival data set that contains actual scores from multidimensional and high-quality assessments of firms and intraorganizational units of a conglomerate business group that had adopted a model of performance excellence for organizational transformation based on the Baldrige criteria. This research …
Secure Mobile Subscription Of Sensor-Encrypted Data, Cheng-Kang Chu, Wen-Tao Zhu, Sherman S. M. Chow, Jianying Zhou, Robert H. Deng
Secure Mobile Subscription Of Sensor-Encrypted Data, Cheng-Kang Chu, Wen-Tao Zhu, Sherman S. M. Chow, Jianying Zhou, Robert H. Deng
Research Collection School Of Computing and Information Systems
In an end-to-end encryption model for a wireless sensor network (WSN), the network control center preloads encryption and decryption keys to the sensor nodes and the subscribers respectively, such that a subscriber can use a mobile device in the deployment field to decrypt the sensed data encrypted by the more resource-constrained sensor nodes. This paper proposes SMS-SED, a provably secure yet practically efficient key assignment system featuring a discrete time-based access control, to better support a business model where the sensors deployer rents the WSN to customers who desires a higher flexibility beyond subscribing to strictly consecutive periods. In SMS-SED, …
Deckard - A Tree-Based, Scalable, And Accurate Code Clone Detection Tool (Version 1.2.1), Lingxiao Jiang, Ghassan Misherghi, Zhendong Su, Glondu Stephane
Deckard - A Tree-Based, Scalable, And Accurate Code Clone Detection Tool (Version 1.2.1), Lingxiao Jiang, Ghassan Misherghi, Zhendong Su, Glondu Stephane
SMU Research Data
Deckard is a tree-based, scalable, and accurate code clone detection tool. It is also capable of reporting clone-related bugs. For more information, pls refer to readme.txt. The latest version is available from Deckard repository on Github. https://github.com/skyhover/Deckard
Artificial Cognitive Memory - Changing From Density Driven To Functionality Driven, Luping Shi, Kaijun Yi, Kiruthika Ramanathan, Rong Zhao, Ning Ning, Ding Ding, Tow Chong Chong
Artificial Cognitive Memory - Changing From Density Driven To Functionality Driven, Luping Shi, Kaijun Yi, Kiruthika Ramanathan, Rong Zhao, Ning Ning, Ding Ding, Tow Chong Chong
Research Collection School Of Computing and Information Systems
Increasing density based on bit size reduction is currently a main driving force for the development of data storage technologies. However, it is expected that all of the current available storage technologies might approach their physical limits in around 15 to 20 years due to miniaturization. To further advance the storage technologies, it is required to explore a new development trend that is different from density driven. One possible direction is to derive insights from biological counterparts. Unlike physical memories that have a single function of data storage, human memory is versatile. It contributes to functions of data storage, information …
Manipulation In Digital Word-Of-Mouth: A Reality Check For Book Reviews, Nan Hu, Indranil Bose, Yunjun Gao, Ling Liu
Manipulation In Digital Word-Of-Mouth: A Reality Check For Book Reviews, Nan Hu, Indranil Bose, Yunjun Gao, Ling Liu
Research Collection School Of Computing and Information Systems
Built upon the discretionary accrual-based earnings management framework, our paper develops a discretionary manipulation proxy to study the management of online reviews. We reveal that fraudulent review manipulation is a serious problem for 1) non-bestseller books; 2) books whose reviews are classified as not very helpful; 3) books that experience greater variability in the helpfulness of their online reviews; and 4) popular books as well as high-priced books. We also show that review management decreases with the passage of time. Just like fraudulent earnings management, manipulated online reviews reflect inauthentic information from which consumers might derive wrong valuation especially for …
Cryptanalysis Of A Certificateless Signcryption Scheme In The Standard Model, Jian Weng, Guoxiang Yao, Robert H. Deng, Min-Rong Chen, Xianxue Li
Cryptanalysis Of A Certificateless Signcryption Scheme In The Standard Model, Jian Weng, Guoxiang Yao, Robert H. Deng, Min-Rong Chen, Xianxue Li
Research Collection School Of Computing and Information Systems
Certificateless signcryption is a useful primitive which simultaneously provides the functionalities of certificateless encryption and certificateless signature. Recently, Liu et al. [15] proposed a new certificateless signcryption scheme, and claimed that their scheme is provably secure without random oracles in a strengthened security model, where the malicious-but-passive KGC attack is considered. Unfortunately, by giving concrete attacks, we indicate that Liu et al. certificateless signcryption scheme is not secure in this strengthened security model.
Pgtp: Power Aware Game Transport Protocol For Multi-Player Mobile Games, Bhojan Anand, Jeena Sebastian, Soh Yu Ming, Akhihebbal L. Ananda, Mun Choon Chan, Rajesh Krishna Balan
Pgtp: Power Aware Game Transport Protocol For Multi-Player Mobile Games, Bhojan Anand, Jeena Sebastian, Soh Yu Ming, Akhihebbal L. Ananda, Mun Choon Chan, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Applications on the smartphones are able to capitalize on the increasingly advanced hardware to provide a user experience reasonably impressive. However, the advancement of these applications are hindered battery lifetime of the smartphones. The battery technologies have a relatively low growth rate. Applications like mobile multiplayer games are especially power hungry as they maximize the use of the network, display and CPU resources. The PGTP, presented in this paper is aware of both the transport requirement of these multiplayer mobile games and the limitation posed by battery resource. PGTP dynamically controls the transport based on the criticality of game state …
Mining Iterative Generators And Representative Rules For Software Specification Discovery, David Lo, Jinyan Li, Limsoon Wong, Siau-Cheng Khoo
Mining Iterative Generators And Representative Rules For Software Specification Discovery, David Lo, Jinyan Li, Limsoon Wong, Siau-Cheng Khoo
Research Collection School Of Computing and Information Systems
Billions of dollars are spent annually on software-related cost. It is estimated that up to 45 percent of software cost is due to the difficulty in understanding existing systems when performing maintenance tasks (i.e., adding features, removing bugs, etc.). One of the root causes is that software products often come with poor, incomplete, or even without any documented specifications. In an effort to improve program understanding, Lo et al. have proposed iterative pattern mining which outputs patterns that are repeated frequently within a program trace, or across multiple traces, or both. Frequent iterative patterns reflect frequent program behaviors that likely …
Mining Social Images With Distance Metric Learning For Automated Image Tagging, Pengcheng Wu, Steven C. H. Hoi, Peilin Zhao, Ying He
Mining Social Images With Distance Metric Learning For Automated Image Tagging, Pengcheng Wu, Steven C. H. Hoi, Peilin Zhao, Ying He
Research Collection School Of Computing and Information Systems
With the popularity of various social media applications, massive social images associated with high quality tags have been made available in many social media web sites nowadays. Mining social images on the web has become an emerging important research topic in web search and data mining. In this paper, we propose a machine learning framework for mining social images and investigate its application to automated image tagging. To effectively discover knowledge from social images that are often associated with multimodal contents (including visual images and textual tags), we propose a novel Unified Distance Metric Learning (UDML) scheme, which not only …
A Two-View Learning Approach For Image Tag Ranking, Jinfeng Zhuang, Steven C. H. Hoi
A Two-View Learning Approach For Image Tag Ranking, Jinfeng Zhuang, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Tags of social images play a central role for text-based social image retrieval and browsing tasks. However, the original tags annotated by web users could be noisy, irrelevant, and often incomplete for describing the image contents, which may severely deteriorate the performance of text-based image retrieval models. In this paper, we aim to overcome the challenge of social tag ranking for a corpus of social images with rich user-generated tags by proposing a novel two-view learning approach. It can effectively exploit both textual and visual contents of social images to discover the complicated relationship between tags and images. Unlike the …
Searching Patterns For Relation Extraction Over The Web: Rediscovering The Pattern-Relation Duality, Yuan Fang, Kevin Chen-Chuan Chang
Searching Patterns For Relation Extraction Over The Web: Rediscovering The Pattern-Relation Duality, Yuan Fang, Kevin Chen-Chuan Chang
Research Collection School Of Computing and Information Systems
While tuple extraction for a given relation has been an active research area, its dual problem of pattern search- to find and rank patterns in a principled way- has not been studied explicitly. In this paper, we propose and address the problem of pattern search, in addition to tuple extraction. As our objectives, we stress reusability for pattern search and scalability of tuple extraction, such that our approach can be applied to very large corpora like the Web. As the key foundation, we propose a conceptual model PRDualRank to capture the notion of precision and recall for both tuples and …
Adnext: A Visit-Pattern-Aware Mobile Advertising System For Urban Commercial Complexes, Byoungjip Kim, Jin-Young Ha, Sangjeong Lee, Seungwoo Kang, Youngki Lee, Yunseok Rhee, Lama Nachman, Junehwa Song
Adnext: A Visit-Pattern-Aware Mobile Advertising System For Urban Commercial Complexes, Byoungjip Kim, Jin-Young Ha, Sangjeong Lee, Seungwoo Kang, Youngki Lee, Yunseok Rhee, Lama Nachman, Junehwa Song
Research Collection School Of Computing and Information Systems
As smartphones have become prevalent, mobile advertising is getting significant attention as being not only a killer application in future mobile commerce, but also as an important business model of emerging mobile applications to monetize them. In this paper, we present AdNext, a visit-pattern-aware mobile advertising system for urban commercial complexes. AdNext can provide highly relevant ads to users by predicting places that the users will next visit. AdNext predicts the next visit place by learning the sequential visit patterns of commercial complex users in a collective manner. As one of the key enabling techniques for AdNext, we develop a …
Distance Metric Learning From Uncertain Side Information For Automated Photo Tagging, Lei Wu, Steven C. H. Hoi, Rong Jin, Jianke Zhu, Nenghai Yu
Distance Metric Learning From Uncertain Side Information For Automated Photo Tagging, Lei Wu, Steven C. H. Hoi, Rong Jin, Jianke Zhu, Nenghai Yu
Research Collection School Of Computing and Information Systems
Automated photo tagging is an important technique for many intelligent multimedia information systems, for example, smart photo management system and intelligent digital media library. To attack the challenge, several machine learning techniques have been developed and applied for automated photo tagging. For example, supervised learning techniques have been applied to automated photo tagging by training statistical classifiers from a collection of manually labeled examples. Although the existing approaches work well for small testbeds with relatively small number of annotation words, due to the long-standing challenge of object recognition, they often perform poorly in large-scale problems. Another limitation of the existing …
Evolution Of Developer Collaboration On The Jazz Platform: A Study Of A Large Scale Agile Project, Subhajit Datta, Renuka Sindhgatta, Bikram Sengupta
Evolution Of Developer Collaboration On The Jazz Platform: A Study Of A Large Scale Agile Project, Subhajit Datta, Renuka Sindhgatta, Bikram Sengupta
Research Collection School Of Computing and Information Systems
Collaboration is a key aspect of the agile philosophy of software development. As a software system matures over iterations, trends of developer collaboration can offer valuable insights into project dynamics. In this paper, we study evolution of developer collaboration for a large scale agile project on the Jazz platform. We construct networks of collaboration based on developer affiliations across comments on work items and file changes; and then compare parameters of such networks with established results from networks of scientific collaborations. The comparisons illuminate interesting facets of developer collaboration on the Jazz platform. Such perception helps deeper understanding of the …
Fraud Detection In Online Consumer Reviews, Nan Hu, Ling Liu, Vallabh Sambamurthy
Fraud Detection In Online Consumer Reviews, Nan Hu, Ling Liu, Vallabh Sambamurthy
Research Collection School Of Computing and Information Systems
Increasingly, consumers depend on social information channels, such as user-posted online reviews, to make purchase decisions. These reviews are assumed to be unbiased reflections of other consumers' experiences with the products or services. While extensively assumed, the literature has not tested the existence or non-existence of review manipulation. By using data from Amazon and Barnes & Noble, our study investigates if vendors, publishers, and writers consistently manipulate online consumer reviews. We document the existence of online review manipulation and show that the manipulation strategy of firms seems to be a monotonically decreasing function of the product's true quality or the …
Fraud Detection In Online Consumer Reviews, Nan Hu, Ling Liu, Vallbh Sambamurthy
Fraud Detection In Online Consumer Reviews, Nan Hu, Ling Liu, Vallbh Sambamurthy
Research Collection School Of Computing and Information Systems
Increasingly, consumers depend on social information channels, such as user-posted online reviews, to make purchase decisions. These reviews are assumed to be unbiased reflections of other consumers' experiences with the products or services. While extensively assumed, the literature has not tested the existence or non-existence of review manipulation. By using data from Amazon and Barnes & Noble, our study investigates if vendors, publishers, and writers consistently manipulate online consumer reviews. We document the existence of online review manipulation and show that the manipulation strategy of firms seems to be a monotonically decreasing function of the product's true quality or the …
Database Access Pattern Protection Without Full-Shuffles, Xuhua Ding, Yanjiang Yang, Robert H. Deng
Database Access Pattern Protection Without Full-Shuffles, Xuhua Ding, Yanjiang Yang, Robert H. Deng
Research Collection School Of Computing and Information Systems
Privacy protection is one of the fundamental security requirements for database outsourcing. A major threat is information leakage from database access patterns generated by query executions. The standard private information retrieval (PIR) schemes, which are widely regarded as theoretical solutions, entail O(n) computational overhead per query for a database with items. Recent works propose to protect access patterns by introducing a trusted component with constant storage size. The resulting privacy assurance is as strong as PIR, though with O(1) online computation cost, they still have O(n) amortized cost per query due to periodically full database shuffles. In this paper, we …
Mining Event Structures From Web Videos, Xiao Wu, Yi-Jie Lu, Qiang Peng, Chong-Wah Ngo
Mining Event Structures From Web Videos, Xiao Wu, Yi-Jie Lu, Qiang Peng, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
The article is discussing the issues of mining event structures from Web video search results using text analysis, burst detection, and clustering as with the proliferation of social media, the volume of Web videos have grown exponentially.
Real-Time Traffic Estimation Using Data Expansion, Roger Lederman, Laura Wynter
Real-Time Traffic Estimation Using Data Expansion, Roger Lederman, Laura Wynter
Research Collection School Of Computing and Information Systems
This paper presents a method for estimating missing real-time traffic volumes on a road network using both historical and real-time traffic data. The method was developed to address urban transportation networks where a non-negligible subset of the network links do not have real-time link volumes, and where that data is needed to populate other real-time traffic analytics. Computation is split between an offline calibration and a real-time estimation phase. The offline phase determines link-to-link splitting probabilities for traffic flow propagation that are subsequently used in real-time estimation. The real-time procedure uses current traffic data and is efficient enough to scale …
Instance-Based Parameter Tuning Via Search Trajectory Similarity Clustering, Linda Lindawati, Hoong Chuin Lau, David Lo
Instance-Based Parameter Tuning Via Search Trajectory Similarity Clustering, Linda Lindawati, Hoong Chuin Lau, David Lo
Research Collection School Of Computing and Information Systems
This paper is concerned with automated tuning of parameters in local-search based meta-heuristics. Several generic approaches have been introduced in the literature that returns a ”one-size-fits-all” parameter configuration for all instances. This is unsatisfactory since different instances may require the algorithm to use very different parameter configurations in order to find good solutions. There have been approaches that perform instance-based automated tuning, but they are usually problem-specific. In this paper, we propose CluPaTra, a generic (problem-independent) approach to perform parameter tuning, based on CLUstering instances with similar PAtterns according to their search TRAjectories. We propose representing a search trajectory as …
Editorial: Special Issue On Ubiquitous Electronic Commerce Systems, Robert H. Deng, Jari Veijalainen, Shiguo Lian, Dimitris Kanellopoulos
Editorial: Special Issue On Ubiquitous Electronic Commerce Systems, Robert H. Deng, Jari Veijalainen, Shiguo Lian, Dimitris Kanellopoulos
Research Collection School Of Computing and Information Systems
Ubiquitous computing is a post-desktop model of human-computer interaction in which information processing has been thoroughly integrated into everyday objects and activities. Emerging ubiquitous electronic commerce systems (UECS) are expected to be available anytime, anywhere, and using different official or personal computing devices. Systems and services such as digital libraries, on-line business transactions, mobile office and mobile TV are widely deployed. Users will be able to access these services anytime, anywhere, while using any computing device in a pervasive way.
Fine-Tuning Algorithm Parameters Using The Design Of Experiments Approach, Aldy Gunawan, Hoong Chuin Lau, Linda Lindawati
Fine-Tuning Algorithm Parameters Using The Design Of Experiments Approach, Aldy Gunawan, Hoong Chuin Lau, Linda Lindawati
Research Collection School Of Computing and Information Systems
Optimizing parameter settings is an important task in algorithm design. Several automated parameter tuning procedures/configurators have been proposed in the literature, most of which work effectively when given a good initial range for the parameter values. In the Design of Experiments (DOE), a good initial range is known to lead to an optimum parameter setting. In this paper, we present a framework based on DOE to find a good initial range of parameter values for automated tuning. We use a factorial experiment design to first screen and rank all the parameters thereby allowing us to then focus on the parameter …
Innovation And Price Competition In A Two-Sided Market, Mei Lin, Shaojin Li, Andrew B. Whinston
Innovation And Price Competition In A Two-Sided Market, Mei Lin, Shaojin Li, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
We examine a platform's optimal two-sided pricing strategy while considering seller-side innovation decisions and price competition. We model the innovation race among sellers in both finite and infinite horizons. In the finite case, we analytically show that the platform's optimal seller-side access fee fully extracts the sellers' surplus, and that the optimal buyer-side access fee mitigates price competition among sellers. The platform's optimal strategy may be to charge or subsidize buyers depending on the degree of variation in the buyers' willingness to pay for quality; this optimal strategy induces full participation on both sides. Furthermore, a wider quality gap among …
Enhancing Bag-Of-Words Models By Efficient Semantics-Preserving Metric Learning, Lei Wu, Steven C. H. Hoi
Enhancing Bag-Of-Words Models By Efficient Semantics-Preserving Metric Learning, Lei Wu, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
The authors present an online semantics preserving, metric learning technique for improving the bag-of-words model and addressing the semantic-gap issue. This article investigates the challenge of reducing the semantic gap for building BoW models for image representation; propose a novel OSPML algorithm for enhancing BoW by minimizing the semantic loss, which is efficient and scalable for enhancing BoW models for large-scale applications; apply the proposed technique for large-scale image annotation and object recognition; and compare it to the state of the art.
An Effective Approach To Pose Invariant 3d Face Recognition, Dayong Wang, Steven C. H. Hoi, Ying He
An Effective Approach To Pose Invariant 3d Face Recognition, Dayong Wang, Steven C. H. Hoi, Ying He
Research Collection School Of Computing and Information Systems
One critical challenge encountered by existing face recognition techniques lies in the difficulties of handling varying poses. In this paper, we propose a novel pose invariant 3D face recognition scheme to improve regular face recognition from two aspects. Firstly, we propose an effective geometry based alignment approach, which transforms a 3D face mesh model to a well-aligned 2D image. Secondly, we propose to represent the facial images by a Locality Preserving Sparse Coding (LPSC) algorithm, which is more effective than the regular sparse coding algorithm for face representation. We conducted a set of extensive experiments on both 2D and 3D …
Real-Time Road Traffic Prediction With Spatio-Temporal Correlations, Wanli Min, Laura Wynter
Real-Time Road Traffic Prediction With Spatio-Temporal Correlations, Wanli Min, Laura Wynter
Research Collection School Of Computing and Information Systems
Real-time road traffic prediction is a fundamental capability needed to make use of advanced, smart transportation technologies. Both from the point of view of network operators as well as from the point of view of travelers wishing real-time route guidance, accurate short-term traffic prediction is a necessary first step. While techniques for short-term traffic prediction have existed for some time, emerging smart transportation technologies require the traffic prediction capability to be both fast and scalable to full urban networks. We present a method that has proven to be able to meet this challenge. The method presented provides predictions of speed …
Trends And Controversies: Ai, Virtual Worlds, And Massively Multiplayer Online Games, Hsinchun Chen, Yulei Zhang, W. S. Bainbridge, Kyong Jin Shim, N. Pathak, M. A. Ahmad, C. Delong, Z. Borbora, A. Mahapatra, J. Srivastava
Trends And Controversies: Ai, Virtual Worlds, And Massively Multiplayer Online Games, Hsinchun Chen, Yulei Zhang, W. S. Bainbridge, Kyong Jin Shim, N. Pathak, M. A. Ahmad, C. Delong, Z. Borbora, A. Mahapatra, J. Srivastava
Research Collection School Of Computing and Information Systems
The rich social media data generated in virtual worlds has important implications for business, education, social science, and society at large. Similarly, massively multiplayer online games (MMOGs) have become increasingly popular and have online communities comprising tens of millions of players. They serve as unprecedented tools for theorizing about and empirically modeling the social and behavioral dynamics of individuals, groups, and networks within large communities. Some technologists consider virtual worlds and MMOGs to be likely candidates to become the Web 3.0. AI can play a significant role, from multiagent avatar research and immersive virtual interface design to virtual world and …