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Articles 5341 - 5370 of 9025

Full-Text Articles in Computer Sciences

On The Security Of Two Identity-Based Conditional Proxy Re-Encryption Schemes, Kai He, Jian Weng, Robert H. Deng, Joseph K. Liu Nov 2016

On The Security Of Two Identity-Based Conditional Proxy Re-Encryption Schemes, Kai He, Jian Weng, Robert H. Deng, Joseph K. Liu

Research Collection School Of Computing and Information Systems

Proxy re-encryption allows a semi-trusted proxy with a re-encryption key to convert a delegator's ciphertext into a delegatee's ciphertext, and the semi-trusted proxy cannot learn anything about the underlying plaintext. If a proxy re-encryption scheme is indistinguishable against chosen-ciphertext attacks, its initialized ciphertext should be non-malleable. Otherwise, there might exist an adversary who can break the chosen-ciphertext security of the scheme. Recently, Liang et al. proposed two proxy re-encryption schemes. They claimed that their schemes were chosen-ciphertext secure in the standard model. However, we find that the original ciphertext in their schemes are malleable. Thus, we present some concrete attacks …

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Privacy-Preserving Outsourced Calculation On Floating Point Numbers, Ximeng Liu, Robert H. Deng, Wenxiu Ding, Rongxing Lu Nov 2016

Privacy-Preserving Outsourced Calculation On Floating Point Numbers, Ximeng Liu, Robert H. Deng, Wenxiu Ding, Rongxing Lu

Research Collection School Of Computing and Information Systems

In this paper, we propose a framework for privacy-preserving outsourced calculation on floating point numbers (POCF). Using POCF, a user can securely outsource the storing and processing of floating point numbers to a cloud server without compromising on the security of the (original) data and the computed results. In particular, we first present privacy-preserving integer processing protocols for common integer operations. We then present an approach to outsourcing floating point numbers for storage in a privacy-preserving way, and securely processing commonly used floating point number operations on-the-fly. We prove that the proposed POCF achieves the goal of floating point number …

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Partitioning Uncertain Workloads, Freddy Chua, Bernardo A. Huberman Nov 2016

Partitioning Uncertain Workloads, Freddy Chua, Bernardo A. Huberman

Research Collection School Of Computing and Information Systems

We present a method for determining the ratio of the tasks when breaking any complex workload in such a way that once the outputs from all tasks are joined, their full completion takes less time and exhibit smaller variance than when running on the undivided workload. To do that, we have to infer the capabilities of the processing unit executing the divided workloads or tasks. We propose a Bayesian Inference algorithm to infer the amount of time each task takes in a way that does not require prior knowledge on the processing unit capability. We demonstrate the effectiveness of this …

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Content Sampling, Household Informedness, And The Consumption Of Digital Information Goods, Ai Phuong Hoang, Robert J. Kauffman Nov 2016

Content Sampling, Household Informedness, And The Consumption Of Digital Information Goods, Ai Phuong Hoang, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

Technology and media are delivering content that is transforming society. Providers must compete for consumer attention to sell their digital information goods effectively. This is challenging, since there is a high level of uncertainty associated with the consumption of such goods. Service providers often use free programming to share product information. We examine the effectiveness of content sampling strategy used for on-demand series dramas, a unique class of entertainment goods. The data were extracted from a large set of household video-on-demand (VoD) viewing records and combined with external data sources. We extended a propensity score matching (PSM) approach to handle …

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Message From The Chairs, Andrew Begel, Fabio Calefato, Christoph Treude Nov 2016

Message From The Chairs, Andrew Begel, Fabio Calefato, Christoph Treude

Research Collection School Of Computing and Information Systems

The Workshop on Social Software Engineering (SSE) focuses on the interplay between social computing and software engineering. On one hand, social factors in software engineering activities, processes and tools are essential for improving the quality of development processes and the software produced by them. Examples include the role of situational awareness and multi-cultural factors in collaborative software development. On the other hand, social software mediates people-to-people communication, supporting human choices, actions, and interactions with each other. Social software needs to accommodate a wide range of social concepts, such as trust, governance, reputation, and privacy. Being social, the software would also …

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Proteus: Computing Disjunctive Loop Summary Via Path Dependency Analysis, Xiaofei Xie, Bihuan Chen, Yang Liu, Wei Le, Xiaohong Li Nov 2016

Proteus: Computing Disjunctive Loop Summary Via Path Dependency Analysis, Xiaofei Xie, Bihuan Chen, Yang Liu, Wei Le, Xiaohong Li

Research Collection School Of Computing and Information Systems

Loops are challenging structures for program analysis, especially when loops contain multiple paths with complex interleaving executions among these paths. In this paper, we first propose a classification of multi-path loops to understand the complexity of the loop execution, which is based on the variable updates on the loop conditions and the execution order of the loop paths. Secondly, we propose a loop analysis framework, named Proteus, which takes a loop program and a set of variables of interest as inputs and summarizes path-sensitive loop effects on the variables. The key contribution is to use a path dependency automaton (PDA) …

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Static Loop Analysis And Its Applications, Xiaofei Xie Nov 2016

Static Loop Analysis And Its Applications, Xiaofei Xie

Research Collection School Of Computing and Information Systems

Loops are challenging structures in program analysis, and an effective loop analysis is crucial in the applications, such as symbolic execution and program verification. In the research, we will first perform a deep analysis and propose a classification according to the complexity of the loops. Then try to propose techniques for analyzing and summarizing different loops. At last, we apply the techniques in multiple applications.

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A Method Of Integrating Correlation Structures For A Generalized Recursive Route Choice Model, Tien Mai Nov 2016

A Method Of Integrating Correlation Structures For A Generalized Recursive Route Choice Model, Tien Mai

Research Collection School Of Computing and Information Systems

We propose a way to estimate a generalized recursive route choice model. The model generalizes other existing recursive models in the literature, i.e., (Fosgerau et al., 2013b; Mai et al., 2015c), while being more flexible since it allows the choice at each stage to be any member of the network multivariate extreme value (network MEV) model (Daly and Bierlaire, 2006). The estimation of the generalized model requires defining a contraction mapping and performing contraction iterations to solve the Bellman’s equation. Given the fact that the contraction mapping is defined based on the choice probability generating functions (CPGF) (Fosgerau et al., …

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A Decomposition Method For Estimating Recursive Logit Based Route Choice Models, Tien Mai, Fabian Bastin, Emma Frejinger Nov 2016

A Decomposition Method For Estimating Recursive Logit Based Route Choice Models, Tien Mai, Fabian Bastin, Emma Frejinger

Research Collection School Of Computing and Information Systems

Fosgerau et al. (2013) recently proposed the recursive logit (RL) model for route choice problems, that can be consistently estimated and easily used for prediction without any sampling of choice sets. Its estimation however requires solving many large-scale systems of linear equations, which can be computationally costly for real data sets. We design a decomposition (DeC) method in order to reduce the number of linear systems to be solved, opening the possibility to estimate more complex RL based models, for instance mixed RL models. We test the performance of the DeC method by estimating the RL model on two networks …

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Hierarchical Visualization Of Video Search Results For Topic-Based Browsing, Yu-Gang Jiang, Jiajun Wang, Qiang Wang, Wei Liu, Chong-Wah Ngo Nov 2016

Hierarchical Visualization Of Video Search Results For Topic-Based Browsing, Yu-Gang Jiang, Jiajun Wang, Qiang Wang, Wei Liu, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Existing video search engines return a ranked list of videos for each user query, which is not convenient for browsing the results of query topics that have multiple facets, such as the "early life," "personal life," and "presidency" of a query "Barack Obama." Organizing video search results into semantically structured hierarchies with nodes covering different topic facets can significantly improve the browsing efficiency for such queries. In this paper, we introduce a hierarchical visualization approach for video search result browsing, which can help users quickly understand the multiple facets of a query topic in a very well-organized manner. Given a …

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Techniques For Identifying Mobile Platform Vulnerabilities And Detecting Policy-Violating Applications, Mon Kywe Su Oct 2016

Techniques For Identifying Mobile Platform Vulnerabilities And Detecting Policy-Violating Applications, Mon Kywe Su

Dissertations and Theses Collection

Mobile systems are generally composed of three layers of software: application layer where third-party applications are installed, framework layer where Application Programming Interfaces (APIs) are exposed, and kernel layer where low-level system operations are executed. In this dissertation, we focus on security and vulnerability analysis of framework and application layers. Security mechanisms, such as Android’s sandbox and permission systems, exist in framework layer, while malware scanners protects application layer. However, there are rooms for improvement in both mechanisms. For instance, Android’s permission system is known to be implemented in ad-hoc manner and not well-tested for vulnerabilities. Application layer also focuses …

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Smu Enhances Curriculum And Expands Offering To Prepare Undergraduates For The Digital Age, Singapore Management University Oct 2016

Smu Enhances Curriculum And Expands Offering To Prepare Undergraduates For The Digital Age, Singapore Management University

SMU Press Releases and News

Demand for infocomm professionals in Singapore is outpacing supply with 30,000 new infocomm jobs expected by 2020. The Infocomm Media 2025 masterplan has identified salient trends that are significant for the next decade, these include Big Data & Analytics, Internet of Things and Cybersecurity. The masterplan also highlighted future key infocomm job areas: Software Development, Cybersecurity, Data Analytics, and Network Infrastructure. In response to these industry trends and demand, SMU has strengthened its undergraduate curriculum in three schools to contribute to the 'future-proofing' of Singapore. The School of Information Systems (SIS) has revised its undergraduate curriculum in response to changes …

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Deep-Based Ingredient Recognition For Cooking Recipe Retrieval, Jingjing Chen, Chong-Wah Ngo Oct 2016

Deep-Based Ingredient Recognition For Cooking Recipe Retrieval, Jingjing Chen, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Retrieving recipes corresponding to given dish pictures facilitates the estimation of nutrition facts, which is crucial to various health relevant applications. The current approaches mostly focus on recognition of food category based on global dish appearance without explicit analysis of ingredient composition. Such approaches are incapable for retrieval of recipes with unknown food categories, a problem referred to as zero-shot retrieval. On the other hand, content-based retrieval without knowledge of food categories is also difficult to attain satisfactory performance due to large visual variations in food appearance and ingredient composition. As the number of ingredients is far less than food …

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Repmatch: Robust Feature Matching And Pose For Reconstructing Modern Cities, Wen-Yan Lin, Siying Liu, Minh N. Do, Ping Tan, Jiangbo Lu Oct 2016

Repmatch: Robust Feature Matching And Pose For Reconstructing Modern Cities, Wen-Yan Lin, Siying Liu, Minh N. Do, Ping Tan, Jiangbo Lu

Research Collection School Of Computing and Information Systems

A perennial problem in recovering 3-D models from images is repeated structures common in modern cities. The problem can be traced to the feature matcher which needs to match less distinctive features (permitting wide-baselines and avoiding broken sequences), while simultaneously avoiding incorrect matching of ambiguous repeated features. To meet this need, we develop RepMatch, an epipolar guided (assumes predominately camera motion) feature matcher that accommodates both wide-baselines and repeated structures. RepMatch is based on using RANSAC to guide the training of match consistency curves for differentiating true and false matches. By considering the set of all nearest-neighbor matches, RepMatch can …

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Determining Quality- And Energy-Aware Multiple Contexts In Pervasive Computing Environments, Nirmalya Roy, Archan Misra, Sajal K. Das, Christine Julien Oct 2016

Determining Quality- And Energy-Aware Multiple Contexts In Pervasive Computing Environments, Nirmalya Roy, Archan Misra, Sajal K. Das, Christine Julien

Research Collection School Of Computing and Information Systems

In pervasive computing environments, understanding the context of an entity is essential for adapting 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 location, activities, social relationships, capabilities, etc. Inherently, however, these high-level context metrics are difficult to capture using uni-modal sensors only and must therefore be inferred using multi-modal sensors. A key challenge in supporting context-aware pervasive computing is how to determine multiple high-level context metrics simultaneously and energy-efficiently using low-level sensor data streams collected from the environment and the entities present therein. A key …

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Integrated Software Fingerprinting Via Neural-Network-Based Control Flow Obfuscation, Haoyu Ma, Ruiqi Li, Xiaoxu Yu, Chunfu Jia, Debin Gao Oct 2016

Integrated Software Fingerprinting Via Neural-Network-Based Control Flow Obfuscation, Haoyu Ma, Ruiqi Li, Xiaoxu Yu, Chunfu Jia, Debin Gao

Research Collection School Of Computing and Information Systems

Dynamic software fingerprinting has been an important tool in fighting against software theft and pirating by embedding unique fingerprints into software copies. However, existing work uses methods from dynamic software watermarking as direct solutions in which secret marks are inside rather independent code modules attached to the software. This results in an intrinsic weakness against targeted collusive attacks since differences among software copies correspond directly to the fingerprint-related components. In this paper, we suggest a novel mode of dynamic fingerprinting called integrated fingerprinting, of which the goal is to ensure all fingerprinted software copies possess identical behaviors at semantic level. …

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When Machine Meets Society: Social Impacts Of Information And Information Economics, Eric K. Clemons, Rajiv M. Dewan, Robert John Kauffman, Thomas A. Weber Oct 2016

When Machine Meets Society: Social Impacts Of Information And Information Economics, Eric K. Clemons, Rajiv M. Dewan, Robert John Kauffman, Thomas A. Weber

Research Collection School Of Computing and Information Systems

No abstract provided.

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Plackett-Luce Regression Mixture Model For Heterogeneous Rankings, Maksim Tkachenko, Hady W. Lauw Oct 2016

Plackett-Luce Regression Mixture Model For Heterogeneous Rankings, Maksim Tkachenko, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Learning to rank is an important problem in many scenarios, such as information retrieval, natural language processing, recommender systems, etc. The objective is to learn a function that ranks a number of instances based on their features. In the vast majority of the learning to rank literature, there is an implicit assumption that the population of ranking instances are homogeneous, and thus can be modeled by a single central ranking function. In this work, we are concerned with learning to rank for a heterogeneous population, which may consist of a number of sub-populations, each of which may rank objects dierently. …

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Achieving Economic And Environmental Sustainabilities In Urban Consolidation Center With Bicriteria Auction, Stephanus Daniel Handoko, Hoong Chuin Lau, Shih-Fen Cheng Oct 2016

Achieving Economic And Environmental Sustainabilities In Urban Consolidation Center With Bicriteria Auction, Stephanus Daniel Handoko, Hoong Chuin Lau, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

Consolidation lies at the heart of the last-mile logistics problem. Urban consolidation centers (UCCs) have been set up to facilitate such consolidation all over the world. To the best of our knowledge, most-if not all-of the UCCs operate on volume-based fixed-rate charges. To achieve environmental sustainability while ensuring economic sustainability in urban logistics, we propose, in this paper, a bicriteria auction mechanism for the automated assignment of last-mile delivery orders to transport resources. We formulate and solve the winner determination problem of the auction as a biobjective programming model. We then present a systematic way to generate the Pareto frontier …

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Dissecting Developer Policy Violating Apps: Characterization And Detection, Su Mon Kywe, Yingjiu Li, Jason Hong, Yao Cheng Oct 2016

Dissecting Developer Policy Violating Apps: Characterization And Detection, Su Mon Kywe, Yingjiu Li, Jason Hong, Yao Cheng

Research Collection School Of Computing and Information Systems

To ensure quality and trustworthiness of mobile apps, Google Play store imposes various developer policies. Once an app is reported for exhibiting policy-violating behaviors, it is removed from the store to protect users. Currently, Google Play store relies on mobile users’ feedbacks to identify policy violations. Our paper takes the first step towards understanding these policy-violating apps. First, we crawl 302 Android apps, which are reported in the Reddit forum by mobile users for policy violations and are later removed from the Google Play store. Second, we perform empirical analysis, which reveals that many violating behaviors have not been studied …

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A Novel Csi Pre-Processing Scheme For Device-Free Localization Indoors, Ju Wang, Lichao Zhang, Xuan Wang, Jie Xiong, Xiaojiang Chen, Dingyi Fang Oct 2016

A Novel Csi Pre-Processing Scheme For Device-Free Localization Indoors, Ju Wang, Lichao Zhang, Xuan Wang, Jie Xiong, Xiaojiang Chen, Dingyi Fang

Research Collection School Of Computing and Information Systems

Device-free localization of people and objects indoors not equipped with radios is playing a critical role in many emerging applications. This paper presents a novel channel state information (CSI) pre-processing scheme that enables accurate device-free localization indoors. The basic idea is simple: CSI is sensitive to a target's location and by modelling the CSI measurements of multiple wireless links as a set of power fading based equations, the target location can be determined. However, due to rich multipaths in indoor environment, the received signal strength (RSS) or even the fine-grained CSI can not be easily modelled. We observe that even …

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Xd-Track: Leveraging Multi-Dimensional Information For Passive Wi-Fi Tracking, Yaxiong Xie, Jie Xiong, Mo Li, Kyle Jamieson Oct 2016

Xd-Track: Leveraging Multi-Dimensional Information For Passive Wi-Fi Tracking, Yaxiong Xie, Jie Xiong, Mo Li, Kyle Jamieson

Research Collection School Of Computing and Information Systems

We describe the design and implementation of xD-Track, the first practical Wi-Fi based device-free localization system that employs a simultaneous and joint estimation of time-of-flight, angle-of-arrival, angle-of-departure, and Doppler shift to fully characterize the wireless channel between a sender and receiver. Using this full characterization, xD-Track introduces novel methods to measure and isolate the signal path that reflects off a person of interest, allowing it to localize a human with just a single pair of access points, or a single client-access point pair. Searching the multiple dimensions to accomplish the above is highly computationally burdensome, so xD-Track introduces novel methods …

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Lifs: Low Human-Effort, Device-Free Localization With Fine-Grained Subcarrier Information, Ju Wang, Hongbo Jiang, Jie Xiong, Kyle Jamieson, Xiaojiang Chen, Dingyi Fang, Binbin Xie Oct 2016

Lifs: Low Human-Effort, Device-Free Localization With Fine-Grained Subcarrier Information, Ju Wang, Hongbo Jiang, Jie Xiong, Kyle Jamieson, Xiaojiang Chen, Dingyi Fang, Binbin Xie

Research Collection School Of Computing and Information Systems

Device-free localization of people and objects indoors not equipped with radios is playing a critical role in many emerging applications. This paper presents an accurate model-based device-free localization system LiFS, implemented on cheap commercial off-the-shelf (COTS) Wi-Fi devices. Unlike previous COTS device-based work, LiFS is able to localize a target accurately without offline training. The basic idea is simple: channel state information (CSI) is sensitive to a target's location and by modelling the CSI measurements of multiple wireless links as a set of power fading based equations, the target location can be determined. However, due to rich multipath propagation indoors, …

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Attribute-Based Encryption With Granular Revocation, Hui Cui, Deng, Robert H., Xuhua Ding, Yingjiu Li Oct 2016

Attribute-Based Encryption With Granular Revocation, Hui Cui, Deng, Robert H., Xuhua Ding, Yingjiu Li

Research Collection School Of Computing and Information Systems

Attribute-based encryption (ABE) enables an access control mechanism over encrypted data by specifying access policies over attributes associated with private keys or ciphertexts, which is a promising solution to protect data privacy in cloud storage services. As an encryption system that involves many data users whose attributes might change over time, it is essential to provide a mechanism to selectively revoke data users’ attributes in an ABE system. However, most of the previous revokable ABE schemes consider how to disable revoked data users to access (newly) encrypted data in the system, and there are few of them that can be …

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Hydra: Massively Compositional Model For Cross-Project Defect Prediction, Xin Xia, David Lo, Sinno Jialin Pan, Nachiappan Nagappan, Xinyu Wang Oct 2016

Hydra: Massively Compositional Model For Cross-Project Defect Prediction, Xin Xia, David Lo, Sinno Jialin Pan, Nachiappan Nagappan, Xinyu Wang

Research Collection School Of Computing and Information Systems

Most software defect prediction approaches are trained and applied on data from the same project. However, often a new project does not have enough training data. Cross-project defect prediction, which uses data from other projects to predict defects in a particular project, provides a new perspective to defect prediction. In this work, we propose a HYbrid moDel Reconstruction Approach (HYDRA) for cross-project defect prediction, which includes two phases: genetic algorithm (GA) phase and ensemble learning (EL) phase. These two phases create a massive composition of classifiers. To examine the benefits of HYDRA, we perform experiments on 29 datasets from the …

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Online Adaptive Passive-Aggressive Methods For Non-Negative Matrix Factorization And Its Applications, Chenghao Liu, Hoi, Steven C. H., Peilin Zhao, Jianling Sun, Ee-Peng Lim Oct 2016

Online Adaptive Passive-Aggressive Methods For Non-Negative Matrix Factorization And Its Applications, Chenghao Liu, Hoi, Steven C. H., Peilin Zhao, Jianling Sun, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

This paper aims to investigate efficient and scalable machine learning algorithms for resolving Non-negative Matrix Factorization (NMF), which is important for many real-world applications, particularly for collaborative filtering and recommender systems. Unlike traditional batch learning methods, a recently proposed online learning technique named "NN-PA" tackles NMF by applying the popular Passive-Aggressive (PA) online learning, and found promising results. Despite its simplicity and high efficiency, NN-PA falls short in at least two critical limitations: (i) it only exploits the first-order information and thus may converge slowly especially at the beginning of online learning tasks; (ii) it is sensitive to some key …

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Attractiveness Versus Competition: Towards An Unified Model For User Visitation, Thanh-Nam Doan, Ee-Peng Lim Oct 2016

Attractiveness Versus Competition: Towards An Unified Model For User Visitation, Thanh-Nam Doan, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Modeling user check-in behavior provides useful insights about venues as well as the users visiting them. These insights can be used in urban planning and recommender system applications. Unlike previous works that focus on modeling distance effect on user’s choice of check-in venues, this paper studies check-in behaviors affected by two venue-related factors, namely, area attractiveness and neighborhood competitiveness. The former refers to the ability of an area with multiple venues to collectively attract checkins from users, while the latter represents the ability of a venue to compete with its neighbors in the same area for check-ins. We first embark …

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Tracking Virality And Susceptibility In Social Media, Tuan Anh Hoang, Ee-Peng Lim Oct 2016

Tracking Virality And Susceptibility In Social Media, Tuan Anh Hoang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

In social media, the magnitude of information propagation hinges on the virality and susceptibility of users spreading and receiving the information respectively, as well as the virality of information items. These users' and items' behavioral factors evolve dynamically at the same time interacting with one another. Previous works however measure the factors statically and independently in a restricted case: each user has only a single adoption on each item, and/or users' exposure to items are observable. In this work, we investigate the inter-relationship among the factors and users' multiple adoptions on items to propose both new static and temporal models …

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Combining Word Embedding With Information Retrieval To Recommend Similar Bug Reports, Xinli Yang, David Lo, Xin Xia, Lingfeng Bao, Jianling Sun Oct 2016

Combining Word Embedding With Information Retrieval To Recommend Similar Bug Reports, Xinli Yang, David Lo, Xin Xia, Lingfeng Bao, Jianling Sun

Research Collection School Of Computing and Information Systems

Similar bugs are bugs that require handling of many common code files. Developers can often fix similar bugs with a shorter time and a higher quality since they can focus on fewer code files. Therefore, similar bug recommendation is a meaningful task which can improve development efficiency. Rocha et al. propose the first similar bug recommendation system named NextBug. Although NextBug performs better than a start-of-the-art duplicated bug detection technique REP, its performance is not optimal and thus more work is needed to improve its effectiveness. Technically, it is also rather simple as it relies only upon a standard information …

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Amalgam+: Composing Rich Information Sources For Accurate Bug Localization, Shaowei Wang, David Lo Oct 2016

Amalgam+: Composing Rich Information Sources For Accurate Bug Localization, Shaowei Wang, David Lo

Research Collection School Of Computing and Information Systems

During the evolution of a software system, a large number of bug reports are submitted. Locating the source code files that need to be fixed to resolve the bugs is a challenging problem. Thus, there is a need for a technique that can automatically figure out these buggy files. A number of bug localization solutions that take in a bug report and output a ranked list of files sorted based on their likelihood to be buggy have been proposed in the literature. However, the accuracy of these tools still needs to be improved. In this paper, to address this need, …

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