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Articles 6241 - 6270 of 8479
Full-Text Articles in Computer Sciences
Authscan: Automatic Extraction Of Web Authentication Protocols From Implementations, Guangdong Bai, Jike Lei, Guozhu Meng, Sai Sathyanarayan Venkatraman, Prateek Saxena, Jun Sun, Yang Liu, Jin Song Dong
Authscan: Automatic Extraction Of Web Authentication Protocols From Implementations, Guangdong Bai, Jike Lei, Guozhu Meng, Sai Sathyanarayan Venkatraman, Prateek Saxena, Jun Sun, Yang Liu, Jin Song Dong
Research Collection School Of Computing and Information Systems
Ideally, security protocol implementations should be formally verified before they are deployed. However, this is not true in practice. Numerous high-profile vulnerabilities have been found in web authentication protocol implementations, especially in single-sign on (SSO) protocols implementations recently. Much of the prior work on authentication protocol verification has focused on theoretical foundations and building scalable verification tools for checking manually-crafted specifications [17, 18, 44]. In this paper, we address a complementary problem of automatically extracting specifications from implementations. We propose AUTHSCAN, an end-to-end platform to automatically recover authentication protocol specifications from their implementations. AUTHSCAN finds a total of 7 security …
Kinectarms: A Toolkit For Capturing And Displaying Arm Embodiments In Distributed Tabletop Groupware, Aaron Genest, Carl Gutwin, Anthony Tang, Michael Kalyn, Zenja Ivkovic
Kinectarms: A Toolkit For Capturing And Displaying Arm Embodiments In Distributed Tabletop Groupware, Aaron Genest, Carl Gutwin, Anthony Tang, Michael Kalyn, Zenja Ivkovic
Research Collection School Of Computing and Information Systems
Gestures are a ubiquitous part of human communication over tables, but when tables are distributed, gestures become difficult to capture and represent. There are several problems: extracting arm images from video, representing the height of the gesture, and making the arm embodiment visible and understandable at the remote table. Current solutions to these problems are often expensive, complex to use, and difficult to set up. We have developed a new toolkit - KinectArms - that quickly and easily captures and displays arm embodiments. KinectArms uses a depth camera to segment the video and determine gesture height, and provides several visual …
Synthetic Controllable Turbulence Using Robust Second Vorticity Confinement, Shengfeng He, Rynson W. H. Lau
Synthetic Controllable Turbulence Using Robust Second Vorticity Confinement, Shengfeng He, Rynson W. H. Lau
Research Collection School Of Computing and Information Systems
Capturing fine details of turbulence on a coarse grid is one of the main tasks in real-time fluid simulation. Existing methods for doing this have various limitations. In this paper, we propose a new turbulence method that uses a refined second vorticity confinement method, referred to as robust second vorticity confinement, and a synthesis scheme to create highly turbulent effects from coarse grid. The new technique is sufficiently stable to efficiently produce highly turbulent flows, while allowing intuitive control of vortical structures. Second vorticity confinement captures and defines the vortical features of turbulence on a coarse grid. However, due to …
Examining Advances In Technology And Hospitality Information Strategy, Robert J. Kauffman, P. Oconnor
Examining Advances In Technology And Hospitality Information Strategy, Robert J. Kauffman, P. Oconnor
Research Collection School Of Computing and Information Systems
Hospitality managers have turned to IT to streamline reservations, capture new customer data, and build market share. Internet-based reservations, advertising and communication, social media, and mobile phones offer technology-led opportunities for value cocreation with customers. We aim to stimulate sharing of new ideas, current applications and emerging managerial know-how for the hospitality industry, while bringing new submissions to CQ.
Online Multiple Kernel Classification, Steven C. H. Hoi, Rong Jin, Peilin Zhao, Tianbao Yang
Online Multiple Kernel Classification, Steven C. H. Hoi, Rong Jin, Peilin Zhao, Tianbao Yang
Research Collection School Of Computing and Information Systems
Although both online learning and kernel learning have been studied extensively in machine learning, there is limited effort in addressing the intersecting research problems of these two important topics. As an attempt to fill the gap, we address a new research problem, termed Online Multiple Kernel Classification (OMKC), which learns a kernel-based prediction function by selecting a subset of predefined kernel functions in an online learning fashion. OMKC is in general more challenging than typical online learning because both the kernel classifiers and the subset of selected kernels are unknown, and more importantly the solutions to the kernel classifiers and …
Online Multi-Modal Distance Learning For Scalable Multimedia Retrieval, Hao Xia, Pengcheng Wu, Steven C. H. Hoi
Online Multi-Modal Distance Learning For Scalable Multimedia Retrieval, Hao Xia, Pengcheng Wu, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
In many real-word scenarios, e.g., multimedia applications, data often originates from multiple heterogeneous sources or are represented by diverse types of representation, which is often referred to as "multi-modal data". The definition of distance between any two objects/items on multi-modal data is a key challenge encountered by many real-world applications, including multimedia retrieval. In this paper, we present a novel online learning framework for learning distance functions on multi-modal data through the combination of multiple kernels. In order to attack large-scale multimedia applications, we propose Online Multi-modal Distance Learning (OMDL) algorithms, which are significantly more efficient and scalable than the …
Combining Crowdsourcing And Google Street View To Identify Street-Level Accessibility Problems, Kotaro Hara, Victoria Le, Jon Froehlich
Combining Crowdsourcing And Google Street View To Identify Street-Level Accessibility Problems, Kotaro Hara, Victoria Le, Jon Froehlich
Research Collection School Of Computing and Information Systems
Jon FroehlichAbstractPoorly maintained sidewalks, missing curb ramps, and other obstacles pose considerable accessibility challenges; however, there are currently few, if any, mechanisms to determine accessible areas of a city a priori. In this paper, we investigate the feasibility of using untrained crowd workers from Amazon Mechanical Turk (turkers) to find, label, and assess sidewalk accessibility problems in Google Street View imagery. We report on two studies: Study 1 examines the feasibility of this labeling task with six dedicated labelers including three wheelchair users; Study 2 investigates the comparative performance of turkers. In all, we collected 13,379 labels and 19,189 verification …
Simple Identity-Based Encryption With Mediated Rsa, Xuhua Ding, Gene Tsudik
Simple Identity-Based Encryption With Mediated Rsa, Xuhua Ding, Gene Tsudik
Research Collection School Of Computing and Information Systems
Identity-based encryption (IBE) [5] and digital signatures are important tools in modern secure communication. In general, identity-based cryptographic methods facilitate easy introduction of public key cryptography by allowing an entity’s public key to be derived from some arbitrary identification value such as an email address or a phone number. Identity-based cryptography greatly reduces the need for, and reliance on, public key certificates. Mediated RSA (mRSA) [4] is a simple and practical method of splitting RSA private keys between the user and the Security Mediator (SEM). Neither the user nor the SEM can cheat one another since each signature or decryption …
Comparing Mobile Privacy Protection Through Cross-Platform Applications, Jin Han, Qiang Yan, Debin Gao, Jianying Zhou, Robert H. Deng
Comparing Mobile Privacy Protection Through Cross-Platform Applications, Jin Han, Qiang Yan, Debin Gao, Jianying Zhou, Robert H. Deng
Research Collection School Of Computing and Information Systems
With the rapid growth of the mobile market, security of mobile platforms is receiving increasing attention from both research community as well as the public. In this paper, we make the first attempt to establish a baseline for security comparison between the two most popular mobile platforms. We investigate applications that run on both Android and iOS and examine the difference in the usage of their security sensitive APIs (SS-APIs). Our analysis over 2,600 applications shows that iOS applications consistently access more SS-APIs than their counterparts on Android. The additional privileges gained on iOS are often associated with accessing private …
I Can Be You: Questioning The Use Of Keystroke Dynamics As Biometrics, Chee Meng Tey, Payas Gupta, Debin Gao
I Can Be You: Questioning The Use Of Keystroke Dynamics As Biometrics, Chee Meng Tey, Payas Gupta, Debin Gao
Research Collection School Of Computing and Information Systems
Keystroke dynamics refer to information about the typing patterns of individuals, such as the relative timing when the individual presses and releases each key. Prior studies suggest that such patterns are unique and cannot be easily imitated. This lays the foundation for the use of keystroke biometrics in authentication systems. The research effort in this area has thus far focused on novel detection techniques to differentiate between legitimate users and imposters. In this paper, we demonstrate a novel feedback and training interface named Mimesis. Mimesis provides both positive and negative feedback on the differences between a submitted pattern vs. a …
Improving Model Checking Stateful Timed Csp With Non-Zenoness Through Clock-Symmetry Reduction, Yuanjie Si, Jun Sun, Yang Liu, Ting Wang
Improving Model Checking Stateful Timed Csp With Non-Zenoness Through Clock-Symmetry Reduction, Yuanjie Si, Jun Sun, Yang Liu, Ting Wang
Research Collection School Of Computing and Information Systems
Real-time system verification must deal with a special notion of ‘fairness’, i.e., clocks must always be able to progress. A system run which prevents clocks from progressing unboundedly is known as Zeno. Zeno runs are infeasible in reality and thus must be pruned during system verification. Though zone abstraction is an effective technique for model checking real-time systems, it is known that zone graphs (e.g., those generated from Timed Automata models) are too abstract to directly infer time progress and hence non-Zenoness. As a result, model checking with non-Zenoness (i.e., existence of a non-Zeno counterexample) based on zone graphs only …
A Utp Semantics For Communicating Processes With Shared Variables, Ling Shi, Yongxin Zhao, Yang Liu, Jun Sun, Jin Song Dong, Shengchao Qin
A Utp Semantics For Communicating Processes With Shared Variables, Ling Shi, Yongxin Zhao, Yang Liu, Jun Sun, Jin Song Dong, Shengchao Qin
Research Collection School Of Computing and Information Systems
CSP# (Communicating Sequential Programs) is a modelling language designed for specifying concurrent systems by integrating CSP-like compositional operators with sequential programs updating shared variables. In this paper, we define an observation-oriented denotational semantics in an open environment for the CSP# language based on the UTP framework. To deal with shared variables, we lift traditional event-based traces into hybrid traces which consist of event-state pairs for recording process behaviours. We also define refinement to check process equivalence and present a set of algebraic laws which are established based on our denotational semantics. Our approach thus provides a rigorous means for reasoning …
Verification Of Functional And Non-Functional Requirements Of Web Service Composition, Manman Chen, Tian Huat Tan, Jun Sun, Yang Liu, Jun Pang, Xiaohong Li
Verification Of Functional And Non-Functional Requirements Of Web Service Composition, Manman Chen, Tian Huat Tan, Jun Sun, Yang Liu, Jun Pang, Xiaohong Li
Research Collection School Of Computing and Information Systems
Web services have emerged as an important technology nowadays. There are two kinds of requirements that are crucial to web service composition, which are functional and non-functional requirements. Functional requirements focus on functionality of the composed service, e.g., given a booking service, an example of functional requirements is that a flight ticket with price higher than $2000 will never be purchased. Non-functional requirements are concerned with the quality of service (QoS), e.g., an example of the booking service’s non-functional requirements is that the service will respond to the user within 5 seconds. Non-functional requirements are important to web service composition, …
Vtrust: A Formal Modeling And Verification Framework For Virtualization Systems, Jianan Hao, Yang Liu, Wentong Cai, Guangdong Bai, Jun Sun
Vtrust: A Formal Modeling And Verification Framework For Virtualization Systems, Jianan Hao, Yang Liu, Wentong Cai, Guangdong Bai, Jun Sun
Research Collection School Of Computing and Information Systems
Virtualization is widely used for critical services like Cloud computing. It is desirable to formally verify virtualization systems. However, the complexity of the virtualization system makes the formal analysis a difficult task, e.g., sophisticated programs to manipulate low-level technologies, paged memory management, memory mapped I/O and trusted computing. In this paper, we propose a formal framework, vTRUST, to formally describe virtualization systems with a carefully designed abstraction. vTRUST includes a library to model configurable hardware components and technologies commonly used in virtualization. The system designer can thus verify virtualization systems on critical properties (e.g., confidentiality, verifiability, isolation and PCR consistency) …
Efficient Salient Region Detection With Soft Image Abstraction, Ming-Ming Cheng, Jonathan Warrell, Wen-Yan Lin, Shuai Zheng, Vibhav Vineet, Nigel Crook
Efficient Salient Region Detection With Soft Image Abstraction, Ming-Ming Cheng, Jonathan Warrell, Wen-Yan Lin, Shuai Zheng, Vibhav Vineet, Nigel Crook
Research Collection School Of Computing and Information Systems
Detecting visually salient regions in images is one of the fundamental problems in computer vision. We propose a novel method to decompose an image into large scale perceptually homogeneous elements for efficient salient region detection, using a soft image abstraction representation. By considering both appearance similarity and spatial distribution of image pixels, the proposed representation abstracts out unnecessary image details, allowing the assignment of comparable saliency values across similar regions, and producing perceptually accurate salient region detection. We evaluate our salient region detection approach on the largest publicly available dataset with pixel accurate annotations. The experimental results show that the …
Robust Non-Parametric Data Fitting For Correspondence Modeling, Wen-Yan Lin, Ming-Ming Cheng, Shuai Zheng, Jiangbo Lu, Nigel Crook
Robust Non-Parametric Data Fitting For Correspondence Modeling, Wen-Yan Lin, Ming-Ming Cheng, Shuai Zheng, Jiangbo Lu, Nigel Crook
Research Collection School Of Computing and Information Systems
We propose a generic method for obtaining nonparametric image warps from noisy point correspondences. Our formulation integrates a huber function into a motion coherence framework. This makes our fitting function especially robust to piecewise correspondence noise (where an image section is consistently mismatched). By utilizing over parameterized curves, we can generate realistic nonparametric image warps from very noisy correspondence. We also demonstrate how our algorithm can be used to help stitch images taken from a panning camera by warping the images onto a virtual push-broom camera imaging plane.
Verifying Linearizability Via Optimized Refinement Checking, Yang Liu, Wei Chen, Yanhong A. Liu, Jun Sun, Shao Jie Zhang, Jin Song Dong Dong
Verifying Linearizability Via Optimized Refinement Checking, Yang Liu, Wei Chen, Yanhong A. Liu, Jun Sun, Shao Jie Zhang, Jin Song Dong Dong
Research Collection School Of Computing and Information Systems
Linearizability is an important correctness criterion for implementations of concurrent objects. Automatic checking of linearizability is challenging because it requires checking that: 1) All executions of concurrent operations are serializable, and 2) the serialized executions are correct with respect to the sequential semantics. In this work, we describe a method to automatically check linearizability based on refinement relations from abstract specifications to concrete implementations. The method does not require that linearization points in the implementations be given, which is often difficult or impossible. However, the method takes advantage of linearization points if they are given. The method is based on …
Modeling And Verifying Hierarchical Real-Time Systems Using Stateful Timed Csp, Jun Sun, Yang Liu, Jin Song Dong, Yan Liu, Ling Shi, Étienne André
Modeling And Verifying Hierarchical Real-Time Systems Using Stateful Timed Csp, Jun Sun, Yang Liu, Jin Song Dong, Yan Liu, Ling Shi, Étienne André
Research Collection School Of Computing and Information Systems
Modeling and verifying complex real-time systems are challenging research problems. The de facto approach is based on Timed Automata, which are finite state automata equipped with clock variables. Timed Automata are deficient in modeling hierarchical complex systems. In this work, we propose a language called Stateful Timed CSP and an automated approach for verifying Stateful Timed CSP models. Stateful Timed CSP is based on Timed CSP and is capable of specifying hierarchical real-time systems. Through dynamic zone abstraction, finite-state zone graphs can be generated automatically from Stateful Timed CSP models, which are subject to model checking. Like Timed Automata, Stateful …
State Space Reduction For Sensor Networks Using Two-Level Partial Order Reduction, Manchun Zheng, David Sanán, Jun Sun, Yang Liu, Jin Song Dong, Yu Gu
State Space Reduction For Sensor Networks Using Two-Level Partial Order Reduction, Manchun Zheng, David Sanán, Jun Sun, Yang Liu, Jin Song Dong, Yu Gu
Research Collection School Of Computing and Information Systems
Wireless sensor networks may be used to conduct critical tasks like fire detection or surveillance monitoring. It is thus important to guarantee the correctness of such systems by systematically analyzing their behaviors. Formal verification of wireless sensor networks is an extremely challenging task as the state space of sensor networks is huge, e.g., due to interleaving of sensors and intra-sensor interrupts. In this work, we develop a method to reduce the state space significantly so that state space exploration methods can be applied to a much smaller state space without missing a counterexample. Our method explores the nature of networked …
Creating Scalable Location-Based Games: Lessons From Geocaching, Carman Neustaedter, Anthony Tang, Tejinder K. Judge
Creating Scalable Location-Based Games: Lessons From Geocaching, Carman Neustaedter, Anthony Tang, Tejinder K. Judge
Research Collection School Of Computing and Information Systems
Location-based games seek to move computer gaming out from behind the PC and into the “real world” of cities, streets, parks, and other locations. This real-world physicality makes the experience fun for game players, yet it brings the unique challenge of creating and orchestrating such a game. That is, location-based games are often difficult to create, grow, and maintain over long periods of time. Our research investigates how location-based games can be designed to overcome this challenge of scalability. We studied the well-established location-based game of Geocaching through active participation and an online survey to better understand how it has …
Moving Object Detection With Laser Scanners, Christoph Mertz, Luis E. Navarro-Serment, Robert Maclachlan, Paul Rybski, Aaron Steinfeld, Arne Suppe, Christopher Urmson, Nicolas Vandapel, Martial Hebert, Chuck Thorpe, David Duggins, Jay Gowdy
Moving Object Detection With Laser Scanners, Christoph Mertz, Luis E. Navarro-Serment, Robert Maclachlan, Paul Rybski, Aaron Steinfeld, Arne Suppe, Christopher Urmson, Nicolas Vandapel, Martial Hebert, Chuck Thorpe, David Duggins, Jay Gowdy
Research Collection School Of Computing and Information Systems
The detection and tracking of moving objects is an essential task in robotics. The CMU-RI Navlab group has developed such a system that uses a laser scanner as its primary sensor. We will describe our algorithm and its use in several applications. Our system worked successfully on indoor and outdoor platforms and with several different kinds and configurations of two-dimensional and three-dimensional laser scanners. The applications vary from collision warning systems, people classification, observing human tracks, and input to a dynamic planner. Several of these systems were evaluated in live field tests and shown to be robust and reliable. (C) …
Technology Investment Decision-Making Under Uncertainty: The Case Of Mobile Payment Systems, Robert J. Kauffman, Jun Liu, Dan Ma
Technology Investment Decision-Making Under Uncertainty: The Case Of Mobile Payment Systems, Robert J. Kauffman, Jun Liu, Dan Ma
Research Collection School Of Computing and Information Systems
The recent launch of Google Wallet has brought the issue of technology solutions in mobile payments (m-payments) to the forefront. In deciding whether and when to adopt m-payments, senior managers in banks are concerned about uncertainties regarding future market conditions, technology standards, and consumer and merchant responses, especially their willingness to adopt. This study applies economic theory and modeling for decision-making under uncertainty to bank investments in m-payment systems technology. We assess the projected benefits and costs of investment as a continuous-time stochastic process to determine optimal investment timing. We find that the value of waiting to adopt jumps when …
Competition Between Software-As-A-Service Vendors, Robert J. Kauffman, Dan Ma
Competition Between Software-As-A-Service Vendors, Robert J. Kauffman, Dan Ma
Research Collection School Of Computing and Information Systems
No abstract provided.
The Pricing Model Of Cloud Computing Services, Jianhui Huang, Dan Ma
The Pricing Model Of Cloud Computing Services, Jianhui Huang, Dan Ma
Research Collection School Of Computing and Information Systems
Cloud computing service providers offer computing resource as a utility and software as a service over network. Many believe that Cloud computing is making an industry-wise paradigm shift for IT use. Besides its technique issues, the business feature of Cloud computing attracts our interests. Specifically the practice of Amazon EC2 introduces an interesting pricing scheme. Amazon provides users with virtual computing instances as a combination of interruptible service (i.e., spot instance) and uninterruptible service (i.e., on-demand and reserved instance). Spot instance is charged at a per use price which is dynamically changing over time; users of spot instance face the …
How Strong Are The Effects Of Technological Disruption? Smartphones' Impacts On Internet And Cable Tv Services Consumption, M. R. Chang, Robert J. Kauffman, K.S. Kim
How Strong Are The Effects Of Technological Disruption? Smartphones' Impacts On Internet And Cable Tv Services Consumption, M. R. Chang, Robert J. Kauffman, K.S. Kim
Research Collection School Of Computing and Information Systems
Emerging technologies have created disruptions in organizational, business process and industry contexts. They act as shocks to a system. We focus on a retail telecom service provider’s offerings of different bun-dles, including mobile phones, Internet and cable TV services. We conduct empirical regularities analysis for Singapore, which was affected by the emergence of smartphones in 2009. We assess the impacts on the service bundle choices of a provider’s customers. We analyze customer switching among service bundles involving three services. We compute switching proba-bilities for each of the service levels offered, as well as between bundles. We use Markov chain transition …
Clustering Of Search Trajectory And Its Application To Parameter Tuning, Linda Lindawati, Hoong Chuin Lau, David Lo
Clustering Of Search Trajectory And Its Application To Parameter Tuning, Linda Lindawati, Hoong Chuin Lau, David Lo
Research Collection School Of Computing and Information Systems
This paper is concerned with automated classification of Combinatorial Optimization Problem instances for instance-specific parameter tuning purpose. We propose the CluPaTra Framework, a generic approach to CLUster instances based on similar PAtterns according to search TRAjectories and apply it on parameter tuning. The key idea is to use the search trajectory as a generic feature for clustering problem instances. The advantage of using search trajectory is that it can be obtained from any local-search based algorithm with small additional computation time. We explore and compare two different search trajectory representations, two sequence alignment techniques (to calculate similarities) as well as …
Multimedia Recommendation: Technology And Techniques, Jialie Shen, Meng Wang, Shuicheng Yan, Peng Cui
Multimedia Recommendation: Technology And Techniques, Jialie Shen, Meng Wang, Shuicheng Yan, Peng Cui
Research Collection School Of Computing and Information Systems
In recent years, we have witnessed a rapid growth in the availability of digital multimedia on various application platforms and domains. Consequently, the problem of information overload has become more and more serious. In order to tackle the challenge, various multimedia recommendation technologies have been developed by different research communities (e.g., multimedia systems, information retrieval, machine learning and computer version). Meanwhile, many commercial web systems (e.g., Flick, YouTube, and Last.fm) have successfully applied recommendation techniques to provide users personalized content and services in a convenient and flexible way. When looking back, the information retrieval (IR) community has a long history …
Towards Next-Generation Multimedia Recommendation Systems, Jialie Shen, Shuicheng Yan, Xian-Sheng Hua
Towards Next-Generation Multimedia Recommendation Systems, Jialie Shen, Shuicheng Yan, Xian-Sheng Hua
Research Collection School Of Computing and Information Systems
Empowered by advances in information technology, such as social media network, digital library and mobile computing, there emerges an ever-increasing amounts of multimedia data. As the key technology to address the problem of information overload, multimedia recommendation system has been received a lot of attentions from both industry and academia. This course aims to 1) provide a series of detailed review of state-of-the-art in multimedia recommendation; 2) analyze key technical challenges in developing and evaluating next generation multimedia recommendation systems from different perspectives and 3) give some predictions about the road lies ahead of us.
Towards Efficient Sparse Coding For Scalable Image Annotation, Junshi Huang, Hairong Liu, Jialie Shen, Shuicheng Yan
Towards Efficient Sparse Coding For Scalable Image Annotation, Junshi Huang, Hairong Liu, Jialie Shen, Shuicheng Yan
Research Collection School Of Computing and Information Systems
Nowadays, content-based retrieval methods are still the development trend of the traditional retrieval systems. Image labels, as one of the most popular approaches for the semantic representation of images, can fully capture the representative information of images. To achieve the high performance of retrieval systems, the precise annotation for images becomes inevitable. However, as the massive number of images in the Internet, one cannot annotate all the images without a scalable and flexible (i.e., training-free) annotation method. In this paper, we particularly investigate the problem of accelerating sparse coding based scalable image annotation, whose off-the-shelf solvers are generally inefficient on …
Hypergraph Index: An Index For Context-Aware Nearest Neighbor Query On Social Networks, Yazhe Wang, Baihua Zheng
Hypergraph Index: An Index For Context-Aware Nearest Neighbor Query On Social Networks, Yazhe Wang, Baihua Zheng
Research Collection School Of Computing and Information Systems
Social network has been touted as the No. 2 innovation in a recent IEEE Spectrum Special Report on “Top 11 Technologies of the Decade”, and it has cemented its status as a bona fide Internet phenomenon. With more and more people starting using social networks to share ideas, activities, events, and interests with other members within the network, social networks contain a huge amount of content. However, it might not be easy to navigate social networks to find specific information. In this paper, we define a new type of queries, namely context-aware nearest neighbor (CANN) search over social network to …