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Articles 5371 - 5400 of 9025

Full-Text Articles in Computer Sciences

Recommending Code Changes For Automatic Backporting Of Linux Device Drivers, Ferdian Thung, Xuan Bach D. Le, David Lo Oct 2016

Recommending Code Changes For Automatic Backporting Of Linux Device Drivers, Ferdian Thung, Xuan Bach D. Le, David Lo

Research Collection School Of Computing and Information Systems

Device drivers are essential components of any operating system (OS). They specify the communication protocol that allows the OS to interact with a device. However, drivers for new devices are usually created for a specific OS version. These drivers often need to be backported to the older versions to allow use of the new device. Backporting is often done manually, and is tedious and error prone. To alleviate this burden on developers, we propose an automatic recommendation system to guide the selection of backporting changes. Our approach analyzes the version history for cues to recommend candidate changes. We have performed …

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Behavior Analysis In Social Networks: Challenges, Technologies, And Trends, Meng Wang, Ee-Peng Lim, Lei Li, Mehmet Orgun Oct 2016

Behavior Analysis In Social Networks: Challenges, Technologies, And Trends, Meng Wang, Ee-Peng Lim, Lei Li, Mehmet Orgun

Research Collection School Of Computing and Information Systems

The research on social networks has advanced significantly, which can be attributed to the prevalence of the online social websites and instant messaging systems as well as the popularity of mobile apps that support easy access to online social networks. These social networks are usually characterized by the complex network structures and rich contextual information. They now become the key platforms for, among others, content dissemination, professional networking, recommendation, alerting, and political campaigns. As online social network users perform activities on the social networks, they leave data traces of human behavior which allow the latter to be studied at scale. …

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Inferring Links Between Concerns And Methods With Multi-Abstraction Vector Space Model, Yun Zhang, David Lo, Xin Xia, Tien-Duy B. Le, Giuseppe Scanniello, Jianling Sun Oct 2016

Inferring Links Between Concerns And Methods With Multi-Abstraction Vector Space Model, Yun Zhang, David Lo, Xin Xia, Tien-Duy B. Le, Giuseppe Scanniello, Jianling Sun

Research Collection School Of Computing and Information Systems

Concern localization refers to the process of locating code units that match a particular textual description. It takes as input textual documents such as bug reports and feature requests and outputs a list of candidate code units that are relevant to the bug reports or feature requests. Many information retrieval (IR) based concern localization techniques have been proposed in the literature. These techniques typically represent code units and textual descriptions as a bag of tokens at one level of abstraction, e.g., each token is a word, or each token is a topic. In this work, we propose a multi-abstraction concern …

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Empirical Study On Synthesis Engines For Semantics-Based Program Repair, Le Dinh Xuan Bach, David Lo, Claire Le Goues Oct 2016

Empirical Study On Synthesis Engines For Semantics-Based Program Repair, Le Dinh Xuan Bach, David Lo, Claire Le Goues

Research Collection School Of Computing and Information Systems

Automatic Program Repair (APR) is an emerging and rapidly growing research area, with many techniques proposed to repair defective software. One notable state-of-the-art line of APR approaches is known as semantics-based techniques, e.g., Angelix, which extract semantics constraints, i.e., specifications, via symbolic execution and test suites, and then generate repairs conforming to these constraints using program synthesis. The repair capability of such approaches-expressive power, output quality, and scalability-naturally depends on the underlying synthesis technique. However, despite recent advances in program synthesis, not much attention has been paid to assess, compare, or leverage the variety of available synthesis engine capabilities in …

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"Automated Debugging Considered Harmful" Considered Harmful: A User Study Revisiting The Usefulness Of Spectra-Based Fault Localization Techniques With Professionals Using Real Bugs From Large Systems, Xin Xia, Lingfeng Bao, David Lo, Shanping Li Oct 2016

"Automated Debugging Considered Harmful" Considered Harmful: A User Study Revisiting The Usefulness Of Spectra-Based Fault Localization Techniques With Professionals Using Real Bugs From Large Systems, Xin Xia, Lingfeng Bao, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Due to the complexity of software systems, bugs are inevitable. Software debugging is tedious and time consuming. To help developers perform this crucial task, a number of spectra-based fault localization techniques have been proposed. In general, spectra-based fault localization helps developers to find the location of a bug given its symptoms (e.g., program failures). A previous study by Parnin and Orso however implies that several assumptions made by existing work on spectra-based fault localization do not hold in practice, which hinders the practical usage of these tools. Moreover, a recent study by Xie et al. claims that spectra-based fault localization …

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Enhancing Automated Program Repair With Deductive Verification, Xuan-Bach D. Le, Quang Loc Le, David Lo, Claire Le Goues Oct 2016

Enhancing Automated Program Repair With Deductive Verification, Xuan-Bach D. Le, Quang Loc Le, David Lo, Claire Le Goues

Research Collection School Of Computing and Information Systems

Automated program repair (APR) is a challenging process of detecting bugs, localizing buggy code, generating fix candidates and validating the fixes. Effectiveness of program repair methods relies on the generated fix candidates, and the methods used to traverse the space of generated candidates to search for the best ones. Existing approaches generate fix candidates based on either syntactic searches over source code or semantic analysis of specification, e.g., test cases. In this paper, we propose to combine both syntactic and semantic fix candidates to enhance the search space of APR, and provide a function to effectively traverse the search space. …

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Arise-Pie: A People Information Integration Engine Over The Web, Vincent W. Zheng, Tao Hoang, Penghe Chen, Yuan Fang, Xiaoyan Yang Oct 2016

Arise-Pie: A People Information Integration Engine Over The Web, Vincent W. Zheng, Tao Hoang, Penghe Chen, Yuan Fang, Xiaoyan Yang

Research Collection School Of Computing and Information Systems

Searching for people information on the Web is a common practice in life. However, it is time consuming to search for such information manually. In this paper, we aim to develop an automatic people information search system, named ARISE-PIE. To build such a system, we tackle two major technical challenges: data harvesting and data integration. For data harvesting, we study how to leverage search engine to help crawl the relevant Web pages for a target entity; then we propose a novel learning to query model that can automatically select a set of "best" queries to maximize collective utility (e.g., precision …

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Bilevel Model-Based Discriminative Dictionary Learning For Recognition, Pan Zhou, Chao Zhang, Lin Zhouchen Oct 2016

Bilevel Model-Based Discriminative Dictionary Learning For Recognition, Pan Zhou, Chao Zhang, Lin Zhouchen

Research Collection School Of Computing and Information Systems

Most supervised dictionary learning methods optimize the combinations of reconstruction error, sparsity prior, and discriminative terms. Thus, the learnt dictionaries may not be optimal for recognition tasks. Also, the sparse codes learning models in the training and the testing phases are inconsistent. Besides, without utilizing the intrinsic data structure, many dictionary learning methods only employ the 0 or 1 norm to encode each datum independently, limiting the performance of the learnt dictionaries. We present a novel bilevel model-based discriminative dictionary learning method for recognition tasks. The upper level directly minimizes the classification error, while the lower level uses the sparsity …

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Satt: Tailoring Code Metric Thresholds For Different Software Architectures, Maurício Aniche, Christoph Treude, Andy Zaidman, Arie Van Deursen, Marco Aurélio Gerosa Oct 2016

Satt: Tailoring Code Metric Thresholds For Different Software Architectures, Maurício Aniche, Christoph Treude, Andy Zaidman, Arie Van Deursen, Marco Aurélio Gerosa

Research Collection School Of Computing and Information Systems

Code metric analysis is a well-known approach for assessing the quality of a software system. However, current tools and techniques do not take the system architecture (e.g., MVC, Android) into account. This means that all classes are assessed similarly, regardless of their specific responsibilities. In this paper, we propose SATT (Software Architecture Tailored Thresholds), an approach that detects whether an architectural role is considerably different from others in the system in terms of code metrics, and provides a specific threshold for that role. We evaluated our approach on 2 different architectures (MVC and Android) in more than 400 projects. We …

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Who Is Who In The Mailing List? Comparing Six Disambiguation Heuristics To Identify Multiple Addresses Of A Participant, Igor Scaliante Wiese, José Teodoro Da Silva, Igor Steinmacher, Christoph Treude, Marco Aurélio Gerosa Oct 2016

Who Is Who In The Mailing List? Comparing Six Disambiguation Heuristics To Identify Multiple Addresses Of A Participant, Igor Scaliante Wiese, José Teodoro Da Silva, Igor Steinmacher, Christoph Treude, Marco Aurélio Gerosa

Research Collection School Of Computing and Information Systems

Many software projects adopt mailing lists for the communication of developers and users. Researchers have been mining the history of such lists to study communities' behavior, organization, and evolution. A potential threat of this kind of study is that users often use multiple email addresses to interact in a single mailing list. This can affect the results and tools, when, for example, extracting social networks. This issue is particularly relevant for popular and long-term Open Source Software (OSS) projects, which attract participation of thousands of people. Researchers have proposed heuristics to identify multiple email addresses from the same participant, however …

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Crowdservice: Serving The Individuals Through Mobile Crowdsourcing And Service Composition, Xin Peng, Jingxiao Gu, Tian Huat Tan, Jun Sun, Yijun Yu, Bashar Nuseibeh, Wenyun Zhao Zhao Sep 2016

Crowdservice: Serving The Individuals Through Mobile Crowdsourcing And Service Composition, Xin Peng, Jingxiao Gu, Tian Huat Tan, Jun Sun, Yijun Yu, Bashar Nuseibeh, Wenyun Zhao Zhao

Research Collection School Of Computing and Information Systems

Some user needs in real life can only be accomplished by leveraging the intelligence and labor of other people via crowdsourcing tasks. For example, one may want to confirm the validity of the description of a secondhand laptop by asking someone else to inspect the laptop on site. To integrate these crowdsourcing tasks into user applications, it is required that crowd intelligence and labor be provided as easily accessible services (e.g., Web services), which can be called crowd services. In this paper, we develop a framework named CROWDSERVICE which supplies crowd intelligence and labor as publicly accessible crowd services via …

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Get Me To My Gate On Time: Efficiently Solving General-Sum Bayesian Threat Screening Games, Aaron Schlenker, Matthew Brown, Arunesh Sinha, Milind Tambe, Ruta Mehta Sep 2016

Get Me To My Gate On Time: Efficiently Solving General-Sum Bayesian Threat Screening Games, Aaron Schlenker, Matthew Brown, Arunesh Sinha, Milind Tambe, Ruta Mehta

Research Collection School Of Computing and Information Systems

Threat Screening Games (TSGs) are used in domains where there is a set of individuals or objects to screen with a limited amount of screening resources available to screen them. TSGs are broadly applicable to domains like airport passenger screening, stadium screening, cargo container screening, etc. Previous work on TSGs focused only on the Bayesian zero-sum case and provided the MGA algorithm to solve these games. In this paper, we solve Bayesian general-sum TSGs which we prove are NP-hard even when exploiting a compact marginal representation. We also present an algorithm based upon a adversary type hierarchical tree decomposition and …

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Human-Centred Design For Silver Assistants, Zhiwei Zheng, Di Wang, Ailiya Borjigin, Chunyan Miao, Ah-Hwee Tan, Cyril Leung Sep 2016

Human-Centred Design For Silver Assistants, Zhiwei Zheng, Di Wang, Ailiya Borjigin, Chunyan Miao, Ah-Hwee Tan, Cyril Leung

Research Collection School Of Computing and Information Systems

To alleviate the rapidly increasing need of the healthcare workforce to serve the enormous ageing population, leveraging intelligent and autonomous caring agents is one promising way. Working towards the design and development of dedicated personal silver assistants for older adults, we follow the human-centred design approach. Specifically, we identify a number of human factors that affect the user experience of the older adults and develop an agent named Mobile Intelligent Silver Assistant (MISA) by applying these human factors. Integrating multiple reusable services onto one platform, MISA acts as a single point of contact while simultaneously providing easy and convenient access …

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Metaflow: A Scalable Metadata Lookup Service For Distributed File Systems In Data Centers, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Haiyong Xie Sep 2016

Metaflow: A Scalable Metadata Lookup Service For Distributed File Systems In Data Centers, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Haiyong Xie

Research Collection School Of Computing and Information Systems

In large-scale distributed file systems, efficient metadata operations are critical since most file operations have to interact with metadata servers first. In existing distributed hash table (DHT) based metadata management systems, the lookup service could be a performance bottleneck due to its significant CPU overhead. Our investigations showed that the lookup service could reduce system throughput by up to 70%, and increase system latency by a factor of up to 8 compared to ideal scenarios. In this paper, we present MetaFlow, a scalable metadata lookup service utilizing software-defined networking (SDN) techniques to distribute lookup workload over network components. MetaFlow tackles …

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Ra2: Predicting Simulation Execution Time For Cloud-Based Design Space Explorations, Nguyen Binh Duong Ta, Wentong Cai, Zengxiang Li, Suiping Zhou Sep 2016

Ra2: Predicting Simulation Execution Time For Cloud-Based Design Space Explorations, Nguyen Binh Duong Ta, Wentong Cai, Zengxiang Li, Suiping Zhou

Research Collection School Of Computing and Information Systems

Design space exploration refers to the evaluation of implementation alternatives for many engineering and design problems. A popular exploration approach is to run a large number of simulations of the actual system with varying sets of configuration parameters to search for the optimal ones. Due to the potentially huge resource requirements, cloud-based simulation execution strategies should be considered in many cases. In this paper, we look at the issue of running largescale simulation-based design space exploration problems on commercial Infrastructure-as-a-Service clouds, namely Amazon EC2, Microsoft Azure and Google Compute Engine. To efficiently manage cloud resources used for execution, the key …

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Incentive Mechanism Design For Heterogeneous Crowdsourcing Using All-Pay Contests, Tie Luo, Salil S. Kanhere, Sajal K. Das, Hwee-Pink Tan Sep 2016

Incentive Mechanism Design For Heterogeneous Crowdsourcing Using All-Pay Contests, Tie Luo, Salil S. Kanhere, Sajal K. Das, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

Many crowdsourcing scenarios are heterogeneous in the sense that, not only the workers' types (e.g., abilities, costs) are different, but the beliefs (probabilistic knowledge) about their respective types are also different. In this paper, we design an incentive mechanism for such scenarios using an asymmetric all-pay contest (or auction) model. Our design objective is an optimal mechanism, i.e., one that maximizes the crowdsourcing revenue minus cost. To achieve this, we furnish the contest with a prize tuple which is an array of reward functions for each potential winner (worker). We prove and characterize the unique equilibrium of this contest, and …

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Autoquery: Automatic Construction Of Dependency Queries For Code Search, Shaowei Wang, David Lo, Lingxiao Jiang Sep 2016

Autoquery: Automatic Construction Of Dependency Queries For Code Search, Shaowei Wang, David Lo, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Many code search techniques have been proposed to return relevant code for a user query expressed as textual descriptions. However, source code is not mere text. It contains dependency relations among various program elements. To leverage these dependencies for more accurate code search results, techniques have been proposed to allow user queries to be expressed as control and data dependency relationships among program elements. Although such techniques have been shown to be effective for finding relevant code, it remains a question whether appropriate queries can be generated by average users. In this work, we address this concern by proposing a …

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Provably Secure Robust Optimistic Fair Exchange Of Distributed Signatures, Yujue Wang, Qianhong Wu, Duncan S. Wong, Bo Qin, Jian Mao, Yong Ding Sep 2016

Provably Secure Robust Optimistic Fair Exchange Of Distributed Signatures, Yujue Wang, Qianhong Wu, Duncan S. Wong, Bo Qin, Jian Mao, Yong Ding

Research Collection School Of Computing and Information Systems

We introduce the concept of optimistic fair exchange of distributed signatures (OFEDS) which allows two groups of parties to fairly exchange digital signatures. Specifically, an authorized set of parties from each group can jointly take part in the protocol on behalf of the affiliated group to fulfill obligation, and a semi-trusted arbitrator will intervene in the protocol only when there are disputes between two sides. Our OFEDS extends the functionality of optimistic fair exchange of threshold signatures to a more generic case. We formalize the security model of OFEDS, in which besides the standard security requirements for existing optimistic fair …

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Improving Carbon Efficiency Through Container Size Optimization And Shipment Consolidation, Nang Laik Ma, Kar Way Tan, Edwin Lik Ming Chong Sep 2016

Improving Carbon Efficiency Through Container Size Optimization And Shipment Consolidation, Nang Laik Ma, Kar Way Tan, Edwin Lik Ming Chong

Research Collection School Of Computing and Information Systems

Purpose: Many manufacturing companies that ship goods through full container loads found themselves under-utilizing the containers and resulting in higher carbon footprint per volume shipment. One of the reasons is the choice of non-ideal container sizes for their shipments. Consolidation fills up the containers more efficiently that reduces the overall carbon footprint. The objective of this paper is to support decisions on selection of appropriate combination of container sizes and shipment consolidation for a manufacturing company. We develop two-steps model which first takes the volumes to be shipped as an input and provide the combination of container sizes required; then …

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Pada: Power-Aware Development Assistant For Mobile Sensing Applications, Chulhong Min, Seungchul Lee, Changhun Lee, Youngki Lee, Seungwoo Kang, Seungpyo Choi, Wonjung Kim, Junehwa Song Sep 2016

Pada: Power-Aware Development Assistant For Mobile Sensing Applications, Chulhong Min, Seungchul Lee, Changhun Lee, Youngki Lee, Seungwoo Kang, Seungpyo Choi, Wonjung Kim, Junehwa Song

Research Collection School Of Computing and Information Systems

We propose PADA, a new power evaluation tool to measure and optimize power use of mobile sensing applications. Our motivational study with 53 professional developers shows they face huge challenges in meeting power requirements. The key challenges are from the significant time and effort for repetitive power measurements since the power use of sensing applications needs to be evaluated under various real-world usage scenarios and sensing parameters. PADA enables developers to obtain enriched power information under diverse usage scenarios in development environments without deploying and testing applications on real phones in real-life situations. We conducted two user studies with 19 …

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Is Only One Gps Point Position Sufficient To Locate You To The Road Network Accurately?, Hao Wu, Weiwei Sun, Baihua Zheng Sep 2016

Is Only One Gps Point Position Sufficient To Locate You To The Road Network Accurately?, Hao Wu, Weiwei Sun, Baihua Zheng

Research Collection School Of Computing and Information Systems

Locating only one GPS position to a road segment accurately is crucial to many location-based services such as mobile taxi-hailing service, geo-tagging, POI check-in, etc. This problem is challenging because of errors including the GPS errors and the digital map errors (misalignment and the same representation of bidirectional roads) and a lack of context information. To the best of our knowledge, no existing work studies this problem directly and the work to reduce GPS signal errors by considering hardware aspect is the most relevant. Consequently, this work is the first attempt to solve the problem of locating one GPS position …

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Server-Aided Revocable Attribute-Based Encryption, Hui Cui, Deng, Robert H., Yingjiu Li, Baodong Qin Sep 2016

Server-Aided Revocable Attribute-Based Encryption, Hui Cui, Deng, Robert H., Yingjiu Li, Baodong Qin

Research Collection School Of Computing and Information Systems

As a one-to-many public key encryption system, attribute-based encryption (ABE) enables scalable access control over encrypted data in cloud storage services. However, efficient user revocation has been a very challenging problem in ABE. To address this issue, Boldyreva, Goyal and Kumar [5] introduced a revocation method by combining the binary tree data structure with fuzzy identity-based encryption, in which a key generation center (KGC) periodically broadcasts key update information to all data users over a public channel. The Boldyreva-Goyal-Kumar approach reduces the size of key updates from linear to logarithm in the number of users, and it has been widely …

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Probabilistic Models For Contextual Agreement In Preferences, Loc Do, Hady W. Lauw Sep 2016

Probabilistic Models For Contextual Agreement In Preferences, Loc Do, Hady W. Lauw

Research Collection School Of Computing and Information Systems

The long-tail theory for consumer demand implies the need for more accurate personalization technologies to target items to the users who most desire them. A key tenet of personalization is the capacity to model user preferences. Most of the previous work on recommendation and personalization has focused primarily on individual preferences. While some focus on shared preferences between pairs of users, they assume that the same similarity value applies to all items. Here we investigate the notion of "context," hypothesizing that while two users may agree on their preferences on some items, they may also disagree on other items. To …

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Modeling Sequential Preferences With Dynamic User And Context Factors, Duc Trong Le, Yuan Fang, Hady W. Lauw Sep 2016

Modeling Sequential Preferences With Dynamic User And Context Factors, Duc Trong Le, Yuan Fang, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Users express their preferences for items in diverse forms, through their liking for items, as well as through the sequence in which they consume items. The latter, referred to as “sequential preference”, manifests itself in scenarios such as song or video playlists, topics one reads or writes about in social media, etc. The current approach to modeling sequential preferences relies primarily on the sequence information, i.e., which item follows another item. However, there are other important factors, due to either the user or the context, which may dynamically affect the way a sequence unfolds. In this work, we develop generative …

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Representation Learning For Homophilic Preferences, Trong T. Nguyen, Hady W. Lauw Sep 2016

Representation Learning For Homophilic Preferences, Trong T. Nguyen, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Users express their personal preferences through ratings, adoptions, and other consumption behaviors. We seek tolearn latent representations for user preferences from such behavioral data. One representation learning model that has been shown to be effective for large preference datasets is Restricted Boltzmann Machine (RBM). While homophily, or the tendency of friends to share their preferences at some level, is an established notion in sociology, thus far it has not yet been clearly demonstrated on RBM-based preference models. The question lies in how to appropriately incorporate social network into the architecture of RBM-based models for learning representations of preferences. In this …

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Tasker: Behavioral Insights Via Campus-Based Experimental Mobile Crowd-Sourcing, Thivya Kandappu, Nikita Jaiman, Randy Tandriansyah Daratan, Archan Misra, Shih-Fen Cheng, Cen Chen, Hoong Chuin Lau, Deepthi Chander, Koustuv Dasgupta Sep 2016

Tasker: Behavioral Insights Via Campus-Based Experimental Mobile Crowd-Sourcing, Thivya Kandappu, Nikita Jaiman, Randy Tandriansyah Daratan, Archan Misra, Shih-Fen Cheng, Cen Chen, Hoong Chuin Lau, Deepthi Chander, Koustuv Dasgupta

Research Collection School Of Computing and Information Systems

While mobile crowd-sourcing has become a game-changer for many urban operations, such as last mile logistics and municipal monitoring, we believe that the design of such crowdsourcing strategies must better accommodate the real-world behavioral preferences and characteristics of users. To provide a real-world testbed to study the impact of novel mobile crowd-sourcing strategies, we have designed, developed and experimented with a real-world mobile crowd-tasking platform on the SMU campus, called TA$Ker. We enhanced the TA$Ker platform to support several new features (e.g., task bundling, differential pricing and cheating analytics) and experimentally investigated these features via a two-month deployment of TA$Ker, …

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An Intelligent System For Personalized Conference Event Recommendation And Scheduling, Aldy Gunawan, Hoong Chuin Lau, Pradeep Varakantham, Wenjie Wang Sep 2016

An Intelligent System For Personalized Conference Event Recommendation And Scheduling, Aldy Gunawan, Hoong Chuin Lau, Pradeep Varakantham, Wenjie Wang

Research Collection School Of Computing and Information Systems

Many conference mobile apps today lack the intelligent feature to automatically generates optimal schedules based on delegates' preferences. This entails two major challenges: (a) identifying preferences of users; and (b) given the preferences, generating a schedule that optimizes his preferences. In this paper, we specifically focus on academic conferences, where users are prompted to input their preferred keywords. Our key contribution is an integrated conference scheduling agent that automatically recognizes user preferences based on keywords, provides a list of recommended talks and optimizes user schedule based on these preferences. To demonstrate the utility of our integrated conference scheduling agent, we …

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A Reinforcement Learning Framework For Trajectory Prediction Under Uncertainty And Budget Constraint, Truc Viet Le, Siyuan Liu, Hoong Chuin Lau Sep 2016

A Reinforcement Learning Framework For Trajectory Prediction Under Uncertainty And Budget Constraint, Truc Viet Le, Siyuan Liu, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We consider the problem of trajectory prediction, where a trajectory is an ordered sequence of location visits and corresponding timestamps. The problem arises when an agent makes sequential decisions to visit a set of spatial locations of interest. Each location bears a stochastic utility and the agent has a limited budget to spend. Given the agent's observed partial trajectory, our goal is to predict the agent's remaining trajectory. We propose a solution framework to the problem that incorporates both the stochastic utility of each location and the budget constraint. We first cluster the agents into groups of homogeneous behaviors called …

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When A Friend Online Is More Than A Friend In Life: Intimate Relationship Prediction In Microblogs, Yunshi Lan, Mengqi Zhang, Feida Zhu, Jing Jiang, Ee-Peng Lim Sep 2016

When A Friend Online Is More Than A Friend In Life: Intimate Relationship Prediction In Microblogs, Yunshi Lan, Mengqi Zhang, Feida Zhu, Jing Jiang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Microblogging services such as Twitter and Sina Weibo have been an important, if not indespensible, platform for people around the world to connect to one another. The rich content and user interactions on these platforms reveal insightful information about each user that are valuable for various real-life applications. In particular, user offline relationships, especially those intimate ones such as family members and couples, offer distinctive value for many business and social settings. In this study, we focus on using Sina Weibo to discover intimate offline relationships among users. The problem is uniquely interesting and challenging due to the difficulty in …

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Dynamic-Music: Accurate Device-Free Indoor Localization, Xiang Li, Shengjie Li, Daqing Zhang, Jie Xiong, Yasha Wang, Hong Mei Sep 2016

Dynamic-Music: Accurate Device-Free Indoor Localization, Xiang Li, Shengjie Li, Daqing Zhang, Jie Xiong, Yasha Wang, Hong Mei

Research Collection School Of Computing and Information Systems

Device-free passive indoor localization is playing a critical role in many applications such as elderly care, intrusion detection, smart home, etc. However, existing device-free localization systems either suffer from labor-intensive offline training or require dedicated special-purpose devices. To address the challenges, we present our system named MaTrack, which is implemented on commodity off-the-shelf Intel 5300 Wi-Fi cards. MaTrack proposes a novel Dynamic-MUSIC method to detect the subtle reflection signals from human body and further differentiate them from those reflected signals from static objects (furniture, walls, etc.) to identify the human target's angle for localization. MaTrack does not require any offline …

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