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Articles 2161 - 2190 of 3560

Full-Text Articles in Databases and Information Systems

Sensorem – An Efficient Mobile Platform For Wireless Sensor Network Visualization, Jin Ming Koh, Marcus Sak, Hwee Xian Tan, Huiguang Liang, Fachmin Folianto, Tony Quek Apr 2015

Sensorem – An Efficient Mobile Platform For Wireless Sensor Network Visualization, Jin Ming Koh, Marcus Sak, Hwee Xian Tan, Huiguang Liang, Fachmin Folianto, Tony Quek

Research Collection School Of Computing and Information Systems

No abstract provided.

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Multi-Roles Affiliation Model For General User Profiling, Lizi Liao, Heyan Huang, Yashen Wang Apr 2015

Multi-Roles Affiliation Model For General User Profiling, Lizi Liao, Heyan Huang, Yashen Wang

Research Collection School Of Computing and Information Systems

Online social networks release user attributes, which is important for many applications. Due to the sparsity of such user attributes online, many works focus on profiling user attributes automatically. However, in order to profile a specific user attribute, an unique model is built and such model usually does not fit other profiling tasks. In our work, we design a novel, flexible general user profiling model which naturally models users’ friendships with user attributes. Experiments show that our method simultaneously profile multiple attributes with better performance.

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Memory Dynamics In Attractor Networks, Guoqi Li, Kiruthika Ramanathan, Ning Ning, Luping Shi, Changyun Wen Apr 2015

Memory Dynamics In Attractor Networks, Guoqi Li, Kiruthika Ramanathan, Ning Ning, Luping Shi, Changyun Wen

Research Collection School Of Computing and Information Systems

As can be represented by neurons and their synaptic connections, attractor networks are widely believed to underlie biological memory systems and have been used extensively in recent years to model the storage and retrieval process of memory. In this paper, we propose a new energy function, which is nonnegative and attains zero values only at the desired memory patterns. An attractor network is designed based on the proposed energy function. It is shown that the desired memory patterns are stored as the stable equilibrium points of the attractor network. To retrieve a memory pattern, an initial stimulus input is presented …

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Best Upgrade Plans For Single And Multiple Source-Destination Pairs, Yimin Lin, Kyriakos Mouratidis Apr 2015

Best Upgrade Plans For Single And Multiple Source-Destination Pairs, Yimin Lin, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

In this paper, we study Resource Constrained Best Upgrade Plan (BUP) computation in road network databases. 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. In the single-pair version of BUP, the input includes a source and a destination in G, and a budget B (resource constraint). The goal is to identify which upgradable edges should be upgraded so that the shortest path distance between source and …

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Review Selection Using Micro-Reviews, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas Apr 2015

Review Selection Using Micro-Reviews, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas

Research Collection School Of Computing and Information Systems

Given the proliferation of review content, and the fact that reviews are highly diverse and often unnecessarily verbose, users frequently face the problem of selecting the appropriate reviews to consume. Micro-reviews are emerging as a new type of online review content in the social media. Micro-reviews are posted by users of check-in services such as Foursquare. They are concise (up to 200 characters long) and highly focused, in contrast to the comprehensive and verbose reviews. In this paper, we propose a novel mining problem, which brings together these two disparate sources of review content. Specifically, we use coverage of micro-reviews …

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Understanding The Test Automation Culture Of App Developers, Pavneet Singh Kochhar, Ferdian. Thung, Nachiappan Nagappan, Thomas Zimmermann, David Lo Apr 2015

Understanding The Test Automation Culture Of App Developers, Pavneet Singh Kochhar, Ferdian. Thung, Nachiappan Nagappan, Thomas Zimmermann, David Lo

Research Collection School Of Computing and Information Systems

Smartphone applications (apps) have gained popularity recently. Millions of smartphone applications (apps) are available on different app stores which gives users plethora of options to choose from, however, it also raises concern if these apps are adequately tested before they are released for public use. In this study, we want to understand the test automation culture prevalent among app developers. Specifically, we want to examine the current state of testing of apps, the tools that are commonly used by app developers, and the problems faced by them. To get an insight on the test automation culture, we conduct two different …

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Mining Business Competitiveness From User Visitation Data, Doan Thanh Nam, Freddy Chong Tat Chua, Ee-Peng Lim Apr 2015

Mining Business Competitiveness From User Visitation Data, Doan Thanh Nam, Freddy Chong Tat Chua, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Ranking businesses by competitiveness is useful in many applications including business (e.g., restaurant) recommendation, and estimation of intrinsic value of businesses for mergers and acquisitions. Our literature reveals that previous methods of business ranking have ignored the competing relationship among businesses within their geographical areas. To account for competition, we propose the use of PageRank model and its variant to derive the Competitive Rankof businesses. We use the check-ins of users from Foursquare, a location-based social network, to model the winners of competitions among stores. The results of our experiments show that Competitive Rank works well when evaluated against ground …

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Exploring Discriminative Features For Anomaly Detection In Public Spaces, Shriguru Nayak, Archan Misra, Kasthuri Jeyarajah, Philips Kokoh Prasetyo, Ee-Peng Lim Apr 2015

Exploring Discriminative Features For Anomaly Detection In Public Spaces, Shriguru Nayak, Archan Misra, Kasthuri Jeyarajah, Philips Kokoh Prasetyo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Context data, collected either from mobile devices or from user-generated social media content, can help identify abnormal behavioural patterns in public spaces (e.g., shopping malls, college campuses or downtown city areas). Spatiotemporal analysis of such data streams provides a compelling new approach towards automatically creating real-time urban situational awareness, especially about events that are unanticipated or that evolve very rapidly. In this work, we use real-life datasets collected via SMU's LiveLabs testbed or via SMU's Palanteer software, to explore various discriminative features (both spatial and temporal - e.g., occupancy volumes, rate of change in topic{specific tweets or probabilistic distribution of …

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Measuring User Influence, Susceptibility And Cynicalness In Sentiment Diffusion, Roy Ka-Wei Lee, Ee Peng Lim Apr 2015

Measuring User Influence, Susceptibility And Cynicalness In Sentiment Diffusion, Roy Ka-Wei Lee, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Diffusion in social networks is an important research topic lately due to massive amount of information shared on social media and Web. As information diffuses, users express sentiments which can affect the sentiments of others. In this paper, we analyze how users reinforce or modify sentiment of one another based on a set of inter-dependent latent user factors as they are engaged in diffusion of event information. We introduce these sentiment-based latent user factors, namely influence, susceptibility and cynicalness. We also propose the ISC model to relate the three factors together and develop an iterative computation approach to …

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Joint Search By Social And Spatial Proximity, Kyriakos Mouratidis, Jing Li, Yu Tang, Nikos Mamoulis Mar 2015

Joint Search By Social And Spatial Proximity, Kyriakos Mouratidis, Jing Li, Yu Tang, Nikos Mamoulis

Research Collection School Of Computing and Information Systems

The diffusion of social networks introduces new challenges and opportunities for advanced services, especially so with their ongoing addition of location-based features. We show how applications like company and friend recommendation could significantly benefit from incorporating social and spatial proximity, and study a query type that captures these two-fold semantics. We develop highly scalable algorithms for its processing, and enhance them with elaborate optimizations. Finally, we use real social network data to empirically verify the efficiency and efficacy of our solutions.

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Reconstruction Privacy: Enabling Statistical Learning, Ke Wang, Chao Han, Ada Waichee Fu, Raymond C. Wong, Philip S. Yu Mar 2015

Reconstruction Privacy: Enabling Statistical Learning, Ke Wang, Chao Han, Ada Waichee Fu, Raymond C. Wong, Philip S. Yu

Research Collection School Of Computing and Information Systems

Non-independent reasoning (NIR) allows the information about one record in the data to be learnt from the information of other records in the data. Most posterior/prior based privacy criteria consider NIR as a privacy violation and require to smooth the distribution of published data to avoid sensitive NIR. The drawback of this approach is that it limits the utility of learning statistical relationships. The differential privacy criterion considers NIR as a non-privacy violation, therefore, enables learning statistical relationships, but at the cost of potential disclosures through NIR. A question is whether it is possible to (1) allow learning statistical relationships, …

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Prediction Of Venues In Foursquare Using Flipped Topic Models, Wen Haw Chong, Bing Tian Dai, Ee Peng Lim Mar 2015

Prediction Of Venues In Foursquare Using Flipped Topic Models, Wen Haw Chong, Bing Tian Dai, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Foursquare is a highly popular location-based social platform, where users indicate their presence at venues via check-ins and/or provide venue-related tips. On Foursquare, we explore Latent Dirichlet Allocation (LDA) topic models for venue prediction: predict venues that a user is likely to visit, given his history of other visited venues. However we depart from prior works which regard the users as documents and their visited venues as terms. Instead we ‘flip’ LDA models such that we regard venues as documents that attract users, which are now the terms. Flipping is simple and requires no changes to the LDA mechanism. Yet …

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Beyond Support And Confidence: Exploring Interestingness Measures For Rule-Based Specification Mining, Bui Tien Duy Le, David Lo Mar 2015

Beyond Support And Confidence: Exploring Interestingness Measures For Rule-Based Specification Mining, Bui Tien Duy Le, David Lo

Research Collection School Of Computing and Information Systems

Numerous rule-based specification mining approaches have been proposed in the literature. Many of these approaches analyze a set of execution traces to discover interesting usage rules, e.g., whenever lock() is invoked, eventually unlock() is invoked. These techniques often generate and enumerate a set of candidate rules and compute some interestingness scores. Rules whose interestingness scores are above a certain threshold would then be output. In past studies, two measures, namely support and confidence, which are well-known measures, are often used to compute these scores. However, aside from these two, many other interestingness measures have been proposed. It is thus unclear …

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On Efficient K-Optimal-Location-Selection Query Processing In Metric Spaces, Yunjun Gao, Shuyao Qi, Lu Chen, Baihua Zheng, Xinhan Li Mar 2015

On Efficient K-Optimal-Location-Selection Query Processing In Metric Spaces, Yunjun Gao, Shuyao Qi, Lu Chen, Baihua Zheng, Xinhan Li

Research Collection School Of Computing and Information Systems

This paper studies the problem of k-optimal-location-selection (kOLS) retrieval in metric spaces. Given a set DA of customers, a set DB of locations, a constrained region R , and a critical distance dc, a metric kOLS (MkOLS) query retrieves k locations in DB that are outside R but have the maximal optimality scores. Here, the optimality score of a location l∈DB located outside R is defined as the number of the customers in DA that are inside R and meanwhile have their distances to l bounded by …

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Nirmal: Automatic Identification Of Software Relevant Tweets Leveraging Language Model, Abishek Sharma, Yuan Tian, David Lo Mar 2015

Nirmal: Automatic Identification Of Software Relevant Tweets Leveraging Language Model, Abishek Sharma, Yuan Tian, David Lo

Research Collection School Of Computing and Information Systems

Twitter is one of the most widely used social media platforms today. It enables users to share and view short 140-character messages called 'tweets'. About 284 million active users generate close to 500 million tweets per day. Such rapid generation of user generated content in large magnitudes results in the problem of information overload. Users who are interested in information related to a particular domain have limited means to filter out irrelevant tweets and tend to get lost in the huge amount of data they encounter. A recent study by Singer et al. found that software developers use Twitter to …

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Use Of A High-Value Social Audience Index For Target Audience Identification On Twitter, Siaw Ling Lo, David Cornforth, Raymond. Chiong Feb 2015

Use Of A High-Value Social Audience Index For Target Audience Identification On Twitter, Siaw Ling Lo, David Cornforth, Raymond. Chiong

Research Collection School Of Computing and Information Systems

With the large and growing user base of social media, it is not an easy feat to identify potential customers for business. This is mainly due to the challenge of extracting commercially viable contents from the vast amount of free-form conversations. In this paper, we analyse the Twitter content of an account owner and its list of followers through various text mining methods and segment the list of followers via an index. We have termed this index as the High-Value Social Audience (HVSA) index. This HVSA index enables a company or organisation to devise their marketing and engagement plan according …

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Privacycanary: Privacy-Aware Recommenders With Adaptive Input Obfuscation, Thivya Kandappu, Arik Friedman, Roksan Borelli, Vijay Sivaraman Feb 2015

Privacycanary: Privacy-Aware Recommenders With Adaptive Input Obfuscation, Thivya Kandappu, Arik Friedman, Roksan Borelli, Vijay Sivaraman

Research Collection School Of Computing and Information Systems

Recommender systems are widely used by online retailers to promote products and content that are most likely to be of interest to a specific customer. In such systems, users often implicitly or explicitly rate products they have consumed, and some form of collaborative filtering is used to find other users with similar tastes to whom the products can be recommended. While users can benefit from more targeted and relevant recommendations, they are also exposed to greater risks of privacy loss, which can lead to undesirable financial and social consequences. The use of obfuscation techniques to preserve the privacy of user …

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Bridging The Vocabulary Gap Between Health Seekers And Healthcare Knowledge, Liqiang Nie, Yiliang Zhao, Akbari Mohammad, Jialie Shen, Tat-Seng Chua Feb 2015

Bridging The Vocabulary Gap Between Health Seekers And Healthcare Knowledge, Liqiang Nie, Yiliang Zhao, Akbari Mohammad, Jialie Shen, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

The vocabulary gap between health seekers and providers has hindered the cross-system operability and the interuser reusability. To bridge this gap, this paper presents a novel scheme to code the medical records by jointly utilizing local mining and global learning approaches, which are tightly linked and mutually reinforced. Local mining attempts to code the individual medical record by independently extracting the medical concepts from the medical record itself and then mapping them to authenticated terminologies. A corpus-aware terminology vocabulary is naturally constructed as a byproduct, which is used as the terminology space for global learning. Local mining approach, however, may …

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Review Synthesis For Micro-Review Summarization, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas Feb 2015

Review Synthesis For Micro-Review Summarization, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas

Research Collection School Of Computing and Information Systems

Micro-reviews is a new type of user-generated content arising from the prevalence of mobile devices and social media in the past few years. Micro-reviews are bite-size reviews (usually under 200 characters), commonly posted on social media or check-in services, using a mobile device. They capture the immediate reaction of users, and they are rich in information, concise, and to the point. However, the abundance of micro-reviews, and their telegraphic nature make it increasingly difficult to go through them and extract the useful information, especially on a mobile device. In this paper, we address the problem of summarizing the micro-reviews of …

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Simapp: A Framework For Detecting Similar Mobile Applications By Online Kernel Learning, Ning Chen, Steven C. H. Hoi, Shaohua Li, Xiaokui Xiao Feb 2015

Simapp: A Framework For Detecting Similar Mobile Applications By Online Kernel Learning, Ning Chen, Steven C. H. Hoi, Shaohua Li, Xiaokui Xiao

Research Collection School Of Computing and Information Systems

With the popularity of smart phones and mobile devices, the number of mobile applications (a.k.a. "apps") has been growing rapidly. Detecting semantically similar apps from a large pool of apps is a basic and important problem, as it is beneficial for various applications, such as app recommendation, app search, etc. However, there is no systematic and comprehensive work so far that focuses on addressing this problem. In order to fill this gap, in this paper, we explore multi-modal heterogeneous data in app markets (e.g., description text, images, user reviews, etc.), and present "SimApp" -- a novel framework for detecting similar …

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On Processing Reverse K-Skyband And Ranked Reverse Skyline Queries, Yunjun Gao, Qing Liu, Baihua Zheng, Mou Li, Gang Chen, Qing Li Feb 2015

On Processing Reverse K-Skyband And Ranked Reverse Skyline Queries, Yunjun Gao, Qing Liu, Baihua Zheng, Mou Li, Gang Chen, Qing Li

Research Collection School Of Computing and Information Systems

In this paper, for the first time, we identify and solve the problem of efficient reverse k-skyband (RkSB) query processing. Given a set P of multi-dimensional points and a query point q, an RkSB query returns all the points in P whose dynamic k-skyband contains q. We formalize RkSB retrieval, and then propose five algorithms for computing the RkSB of an arbitrary query point efficiently. Our methods utilize a conventional data-partitioning index (e.g., R-tree) on the dataset, and employ pre-computation, reuse and pruning techniques to boost the query efficiency. In addition, we extend our solutions to tackle an interesting variant …

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The Power Of Technology In Cre Data And Analytics, Clarence Goh Jan 2015

The Power Of Technology In Cre Data And Analytics, Clarence Goh

Research Collection School of Accountancy

Many companies are using data to drive competitiveadvantage. Across industries, there is rapidly growingappreciation that data-driven insights can substantiallyimprove decision making across a wide range of businessfunctions, and corporate real estate (CRE) is no exception.

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Modeling Neuromorphic Persistent Firing Networks, Ning Ning, Guoqi Li, Wei He, Kejie Huang, Li Pan, Kiruthika Ramanathan, Rong Zhao, Luping Shi Jan 2015

Modeling Neuromorphic Persistent Firing Networks, Ning Ning, Guoqi Li, Wei He, Kejie Huang, Li Pan, Kiruthika Ramanathan, Rong Zhao, Luping Shi

Research Collection School Of Computing and Information Systems

Neurons are believed to be the brain computational engines of the brain. A recent discovery in neurophysiology reveals that interneurons can slowly integrate spiking, share the output across a coupled network of axons and respond with persistent firing even in the absence of input to the soma or dendrites, which has not been understood and could be very important for exploring the mechanism of human cognition. The conventional models are incapable of simulating the important newly-discovered phenomenon of persistent firing induced by axonal slow integration. In this paper, we propose a computationally efficient model of neurons through modeling the axon …

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Toward Mobile Robots Reasoning Like Humans, Jean Oh, Arne Suppe, Felix Duvallet, Abdeslam Boularias, Luis Navarro-Serment, Martial Hebert, Anthony Stentz, Jerry Vinokurov, Oscar Romero, Christian Lebiere, Robert Dean Jan 2015

Toward Mobile Robots Reasoning Like Humans, Jean Oh, Arne Suppe, Felix Duvallet, Abdeslam Boularias, Luis Navarro-Serment, Martial Hebert, Anthony Stentz, Jerry Vinokurov, Oscar Romero, Christian Lebiere, Robert Dean

Research Collection School Of Computing and Information Systems

Robots are increasingly becoming key players in human-robot teams. To become effective teammates, robots must possess profound understanding of an environment, be able to reason about the desired commands and goals within a specific context, and be able to communicate with human teammates in a clear and natural way. To address these challenges, we have developed an intelligence architecture that combines cognitive components to carry out high-level cognitive tasks, semantic perception to label regions in the world, and a natural language component to reason about the command and its relationship to the objects in the world. This paper describes recent …

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Integrated Intelligence For Human-Robot Teams, Jean Oh, Et. Al. Jan 2015

Integrated Intelligence For Human-Robot Teams, Jean Oh, Et. Al.

Research Collection School Of Computing and Information Systems

With recent advances in robotics technologies and autonomous systems, the idea of human-robot teams is gaining ever-increasing attention. In this context, our research focuses on developing an intelligent robot that can autonomously perform non-trivial, but specific tasks conveyed through natural language. Toward this goal, a consortium of researchers develop and integrate various types of intelligence into mobile robot platforms, including cognitive abilities to reason about high-level missions, perception to classify regions and detect relevant objects in an environment, and linguistic abilities to associate instructions with the robot’s world model and to communicate with human teammates in a natural way. This …

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Saliency-Guided Color-To-Gray Conversion Using Region-Based Optimization, Hao Du, Shengfeng He, Bin Sheng, Lizhuang Ma, Rynson W.H. Lau Jan 2015

Saliency-Guided Color-To-Gray Conversion Using Region-Based Optimization, Hao Du, Shengfeng He, Bin Sheng, Lizhuang Ma, Rynson W.H. Lau

Research Collection School Of Computing and Information Systems

Image decolorization is a fundamental problem for many real-world applications, including monochrome printing and photograph rendering. In this paper, we propose a new color-to-gray conversion method that is based on a region-based saliency model. First, we construct a parametric color-to-gray mapping function based on global color information as well as local contrast. Second, we propose a region-based saliency model that computes visual contrast among pixel regions. Third, we minimize the salience difference between the original color image and the output grayscale image in order to preserve contrast discrimination. To evaluate the performance of the proposed method in preserving contrast in …

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Community Discovery From Social Media By Low-Rank Matrix Recovery, Jinfeng Zhuang, Mei Tao, Steven C. H. Hoi, Xian-Sheng Hua, Yongdong Zhang Jan 2015

Community Discovery From Social Media By Low-Rank Matrix Recovery, Jinfeng Zhuang, Mei Tao, Steven C. H. Hoi, Xian-Sheng Hua, Yongdong Zhang

Research Collection School Of Computing and Information Systems

The pervasive usage and reach of social media have attracted a surge of attention in the multimedia research community. Community discovery from social media has therefore become an important yet challenging issue. However, due to the subjective generating process, the explicitly observed communities (e.g., group-user and user-user relationship) are often noisy and incomplete in nature. This paper presents a novel approach to discovering communities from social media, including the group membership and user friend structure, by exploring a low-rank matrix recovery technique. In particular, we take Flickr as one exemplary social media platform. We first model the observed indicator matrix …

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Special Section: Economics, Electronic Commerce, And Competitive Strategy, Eric K. Clemons, Rajiv M. Dewan, Robert John Kauffman Jan 2015

Special Section: Economics, Electronic Commerce, And Competitive Strategy, Eric K. Clemons, Rajiv M. Dewan, Robert John Kauffman

Research Collection School Of Computing and Information Systems

The title of this year;s special section of selected papers, whose initial versionswere presented at the “Economics and Electronic Commerce,” and “Information Technologyand Competitive Strategy” mini-tracks of the 2001 Hawaii International Conferenceon Systems Science (HICSS), reflects the increasing convergence of ideas fromEconomics and Information Systems (IS) research. This convergence has been occurringover the last several years and is related to the developments in e-commerce. ISresearch has been rapidly coming of age, driven by the ever-increasing importance ofinformation technology (IT) in the marketplace, and the need for managers, investors,policy-makers, and the public to understand how to more effectively navigate in ourhighly …

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Reputationpro: The Efficient Approaches To Contextual Transaction Trust Computation In E-Commerce Environments, Haibin Zhang, Yan Wang, Xiuzhen Zhang, Ee Peng Lim Jan 2015

Reputationpro: The Efficient Approaches To Contextual Transaction Trust Computation In E-Commerce Environments, Haibin Zhang, Yan Wang, Xiuzhen Zhang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

In e-commerce environments, the trustworthiness of a seller is utterly important to potential buyers, especially when a seller is not known to them. Most existing trust evaluation models compute a single value to reflect the general trustworthiness of a seller without taking any transaction context information into account. With such a result as the indication of reputation, a buyer may be easily deceived by a malicious seller in a transaction where the notorious value imbalance problem is involved—in other words, a malicious seller accumulates a high-level reputation by selling cheap products and then deceives buyers by inducing them to purchase …

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Multidimensional Context Awareness In Mobile Devices, Zhuo Wei, Robert H. Deng, Jialie Shen, Jixiang Zhu, Kun Ouyang, Yongdong Wu Jan 2015

Multidimensional Context Awareness In Mobile Devices, Zhuo Wei, Robert H. Deng, Jialie Shen, Jixiang Zhu, Kun Ouyang, Yongdong Wu

Research Collection School Of Computing and Information Systems

With the increase of mobile computation ability and the development of wireless network transmission technology, mobile devices not only are the important tools of personal life (e.g., education and entertainment), but also emerge as indispensable "secretary" of business activities (e.g., email and phone call). However, since mobile devices could work under complex and dynamic local and network conditions, they are vulnerable to local and remote security attacks. In real applications, different kinds of data protection are required by various local contexts. To provide appropriate protection, we propose a multidimensional context (MContext) scheme to comprehensively model and characterize the scene and …

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