Joint Optimization Of Resource Provisioning In Cloud Computing,
2017
Singapore Management University
Joint Optimization Of Resource Provisioning In Cloud Computing, Jonathan David Chase, Dusit Niyato
Research Collection School Of Computing and Information Systems
Cloud computing exploits virtualization to provision resources efficiently. Increasingly, Virtual Machines (VMs) have high bandwidth requirements; however, previous research does not fully address the challenge of both VM and bandwidth provisioning. To efficiently provision resources, a joint approach that combines VMs and bandwidth allocation is required. Furthermore, in practice, demand is uncertain. Service providers allow the reservation of resources. However, due to the dangers of over-and under-provisioning, we employ stochastic programming to account for this risk. To improve the efficiency of the stochastic optimization, we reduce the problem space with a scenario tree reduction algorithm, that significantly increases tractability, whilst …
Neural Correlates Of User Experience In Gaming,
2017
Singapore Management University
Neural Correlates Of User Experience In Gaming, Y. Tejaswini, F. Nah, Keng Siau, L. Chen
Research Collection School Of Computing and Information Systems
The objective of this research is to understand the neural correlates of user states of experience in human-computer interaction using electroencephalogram (EEG). Such user states include flow, boredom, and anxiety that are experienced when a user interacts with a computer-based system. We propose using a within-subjects experiment to collect EEG data to assess and compare the neural correlates of three main states of user experience (i.e., flow, boredom, and anxiety) as well as compare them with the resting state as a baseline. We expect the findings from this research to contribute to an improved understanding of psychophysiological means of assessing …
Effects Of The Use Of Leaderboards In Education,
2017
Singapore Management University
Effects Of The Use Of Leaderboards In Education, Yu-Hsien Chiu, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Gamification has been used in education to increase student motivation and performance. In this research, we are interested to examine the effect of leaderboards on student motivation by assessing the interest of students to complete optional practice questions provided to them in a course. Based on goal setting theory and cognitive evaluation theory, we hypothesize that the use of leaderboards will lead to increased student motivation. We designed a within-subject experiment where leaderboards were not provided in the first half of the semester for the optional assignments comprising practice questions but were provided in the second half of the semester …
The Impact Of Monetary Value Gains And Losses On Cybersecurity Behavior,
2017
Singapore Management University
The Impact Of Monetary Value Gains And Losses On Cybersecurity Behavior, Samuel Noah Smith, Fiona Fui-Hoon Nah, Maggie Cheng, Santosh Kuma Ravindran
Research Collection School Of Computing and Information Systems
This research examines if users take more risky cybersecurity actions when presented with the possibility of losing monetary value rather than gaining monetary value. Prospect theory provides the theoretical foundation for the research. An experimental design is proposed to test the hypothesis for the research.
Real-Time Prediction Of Length Of Stay Using Passive Wi-Fi Sensing,
2017
Singapore Management University
Real-Time Prediction Of Length Of Stay Using Passive Wi-Fi Sensing, Truc Viet Le, Baoyang Song, Laura Wynter
Research Collection School Of Computing and Information Systems
The proliferation of wireless technologies in today's everyday life is one of the key drivers of the Internet of Things (IoT). In addition to being an enabler of connectivity, the vast penetration of wireless devices today gives rise to a secondary functionality as a means of tracking and localization of the devices themselves. Indeed, in order to discover and automatically connect to known Wi-Fi networks, mobile devices have to scan and broadcast the so-called probe requests on all available channels, which can be captured and analyzed in a non-intrusive manner. Thus, one of the key applications of this feature is …
Lexicons In Sentiment Analytics,
2017
Singapore Management University
Lexicons In Sentiment Analytics, B. Yuan, Keng Siau
Research Collection School Of Computing and Information Systems
With the increasing amount of text data, sentiment analytics (SA) is becoming an important tool for text miners. An automated approach is needed to parse the online reviews and comments, and analyze their sentiments. Since lexicon is the most important component in SA, enhancing the quality of lexicons will improve the efficiency and accuracy of sentiment analysis. In this research, we study the effect of coupling a general lexicon with a specialized lexicon (for a specific domain) and its impact on sentiment analysis. Two special domains and one general domain were used. The two special domains are the petroleum domain …
Encrypted Data Processing With Homomorphic Re-Encryption,
2017
Xidian University
Encrypted Data Processing With Homomorphic Re-Encryption, Wenxiu Ding, Zheng Yan, Robert H. Deng
Research Collection School Of Computing and Information Systems
Cloud computing offers various services to users by re-arranging storage and computing resources. In order to preserve data privacy, cloud users may choose to upload encrypted data rather than raw data to the cloud. However, processing and analyzing encrypted data are challenging problems, which have received increasing attention in recent years. Homomorphic Encryption (HE) was proposed to support computation on encrypted data and ensure data confidentiality simultaneously. However, a limitation of HE is it is a single user system, which means it only allows the party that owns a homomorphic decryption key to decrypt processed ciphertexts. Original HE cannot support …
Impact Of Artificial Intelligence, Robotics, And Machine Learning On Sales And Marketing,
2017
Singapore Management University
Impact Of Artificial Intelligence, Robotics, And Machine Learning On Sales And Marketing, Keng Siau, Y. Yang
Research Collection School Of Computing and Information Systems
AI, robotics, and machine learning are impacting the field of sales and marketing in an unprecedented way. A perfect storm is brewing! On one hand, online retail stores like Amazon are crushing the bricks and mortar stores. Sales and marketing professionals in bricks and mortar stores are facing a grim future. On the other hand, AI, robotics, and machine learning are replacing sales and marketing professionals in online stores. In fact, salespersons and marketers are predicted to be among the first to be replaced by robots. In a face-to-face environment, human may still prefer to interact with another human. In …
Machine Learning Approaches To Sentiment Analytics,
2017
Singapore Management University
Machine Learning Approaches To Sentiment Analytics, W. Zhao, Keng Siau
Research Collection School Of Computing and Information Systems
One key aspect of sentiment analytics is emotion classification. This research studies the use of machine learning approaches to classify human emotion. Two different machine learning approaches were compared in an experimental study. In one approach, emotions from both genders were used to train the machine. In another approach, genders were separated and two separate machines were used to learn the emotions of the two genders. We also manipulated the training sample sizes and study the effect of training sample sizes on the two machine learning approaches. Our preliminary results show that the approach where the genders were separated produces …
Exploiting Contextual Information For Fine-Grained Tweet Geolocation,
2017
Singapore Management University
Exploiting Contextual Information For Fine-Grained Tweet Geolocation, Wen Haw Chong, Ee Peng Lim
Research Collection School Of Computing and Information Systems
The problem of fine-grained tweet geolocation is to link tweets to their posting venues. We solve this in a learning to rank framework by ranking candidate venues given a test tweet. The problem is challenging as tweets are short and the vast majority are non-geocoded, meaning information is sparse for building models. Nonetheless, although only a small fraction of tweets are geocoded, we find that they are posted by a substantial proportion of users. Essentially, such users have location history data. Along with tweet posting time, these serve as additional contextual information for geolocation. In designing our geolocation models, we …
Collaborative Topic Regression For Online Recommender Systems: An Online And Bayesian Approach,
2017
Zhejiang University
Collaborative Topic Regression For Online Recommender Systems: An Online And Bayesian Approach, Chenghao Liu, Tao Jin, Steven C. H. Hoi, Peilin Zhao, Jianling Sun
Research Collection School Of Computing and Information Systems
Collaborative Topic Regression (CTR) combines ideas of probabilistic matrix factorization (PMF) and topic modeling (such as LDA) for recommender systems, which has gained increasing success in many applications. Despite enjoying many advantages, the existing Batch Decoupled Inference algorithm for the CTR model has some critical limitations: First of all, it is designed to work in a batch learning manner, making it unsuitable to deal with streaming data or big data in real-world recommender systems. Secondly, in the existing algorithm, the item-specific topic proportions of LDA are fed to the downstream PMF but the rating information is not exploited in discovering …
Data-Driven Approach To Measuring The Level Of Press Freedom Using Media Attention Diversity From Unfiltered News,
2017
Singapore Management University
Data-Driven Approach To Measuring The Level Of Press Freedom Using Media Attention Diversity From Unfiltered News, Jisun An, Haewoon Kwak
Research Collection School Of Computing and Information Systems
Published by Reporters Without Borders every year, the Press Freedom Index (PFI) reflects the fear and tension in the newsroom pushed by the government and private sectors. While the PFI is invaluable in monitoring media environ- ments worldwide, the current survey-based method has in- herent limitations to updates in terms of cost and time. In this work, we introduce an alternative way to measure the level of press freedom using media attention diversity compiled from Unfiltered News.
Dpweka: Achieving Differential Privacy In Weka,
2017
University of Arkansas, Fayetteville
Dpweka: Achieving Differential Privacy In Weka, Srinidhi Katla
Graduate Theses and Dissertations
Organizations belonging to the government, commercial, and non-profit industries collect and store large amounts of sensitive data, which include medical, financial, and personal information. They use data mining methods to formulate business strategies that yield high long-term and short-term financial benefits. While analyzing such data, the private information of the individuals present in the data must be protected for moral and legal reasons. Current practices such as redacting sensitive attributes, releasing only the aggregate values, and query auditing do not provide sufficient protection against an adversary armed with auxiliary information. In the presence of additional background information, the privacy protection …
Discovering Your Selling Points: Personalized Social Influential Tags Exploration,
2017
Singapore Management University
Discovering Your Selling Points: Personalized Social Influential Tags Exploration, Yuchen Li, Kian-Lee Tan, Ju Fan, Dongxiang Zhang
Research Collection School Of Computing and Information Systems
Social influence has attracted significant attention owing to the prevalence of social networks (SNs). In this paper, we study a new social influence problem, called personalized social influential tags exploration (PITEX), to help any user in the SN explore how she influences the network. Given a target user, it finds a size-k tag set that maximizes this user’s social influence. We prove the problem is NP-hard to be approximated within any constant ratio. To solve it, we introduce a sampling-based framework, which has an approximation ratio of 1−ǫ 1+ǫ with high probabilistic guarantee. To speedup the computation, we devise more …
Dynamic Nearest Neighbor Queries In Euclidean Space,
2017
City University of Hong Kong
Dynamic Nearest Neighbor Queries In Euclidean Space, Sarana Nutanong, Mohammed Eunus Ali, Egemen Tanin, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
Given a query point q and a set D of data points, a nearest neighbor (NN) query returns the data point p in D that minimizes the distance DIST(q,p), where the distance function DIST(,) is the L2norm. One important variant of this query type is kNN query, which returns k data points with the minimum distances. When taking the temporal dimension into account, the k NN query result may change over a period of time due to changes in locations of the query point and/or data points.
Continuous Top-K Monitoring On Document Streams,
2017
University of Macau
Continuous Top-K Monitoring On Document Streams, Leong Hou U, Junjie Zhang, Kyriakos Mouratidis, Ye Li
Research Collection School Of Computing and Information Systems
The efficient processing of document streams plays an important role in many information filtering systems. Emerging applications, such as news update filtering and social network notifications, demand presenting end-users with the most relevant content to their preferences. In this work, user preferences are indicated by a set of keywords. A central server monitors the document stream and continuously reports to each user the top-k documents that are most relevant to her keywords. Our objective is to support large numbers of users and high stream rates, while refreshing the top-k results almost instantaneously. Our solution abandons the traditional frequency-ordered indexing approach. …
A Data-Driven Approach For Benchmarking Energy Efficiency Of Warehouse Buildings,
2017
Singapore Management University
A Data-Driven Approach For Benchmarking Energy Efficiency Of Warehouse Buildings, Wee Leong Lee, Kar Way Tan, Zui Young Lim
Research Collection School Of Computing and Information Systems
This study proposes adata-driven approach for benchmarking energy efficiency of warehouse buildings.Our proposed approach provides an alternative to the limitation of existingbenchmarking approaches where a theoretical energy-efficient warehouse was usedas a reference. Our approach starts by defining the questions needed to capturethe characteristics of warehouses relating to energy consumption. Using an existingdata set of warehouse building containing various attributes, we first cluster theminto groups by their characteristics. The warehouses characteristics derivedfrom the cluster assignments along with their past annual energy consumptionare subsequently used to train a decision tree model. The decision tree providesa classification of what factors contribute to different …
A Neural Network Model For Semi-Supervised Review Aspect Identification,
2017
Singapore Management University
A Neural Network Model For Semi-Supervised Review Aspect Identification, Ying Ding, Changlong Yu, Jing Jiang
Research Collection School Of Computing and Information Systems
Aspect identification is an important problem in opinion mining. It is usually solved in an unsupervised manner, and topic models have been widely used for the task. In this work, we propose a neural network model to identify aspects from reviews by learning their distributional vectors. A key difference of our neural network model from topic models is that we do not use multinomial word distributions but instead embedding vectors to generate words. Furthermore, to leverage review sentences labeled with aspect words, a sequence labeler based on Recurrent Neural Networks (RNNs) is incorporated into our neural network. The resulting model …
Determining The Impact Regions Of Competing Options In Preference Space,
2017
Singapore Management University
Determining The Impact Regions Of Competing Options In Preference Space, Bo Tang, Kyriakos Mouratidis, Man Lung. Yiu
Research Collection School Of Computing and Information Systems
In rank-aware processing, user preferences are typically represented by a numeric weight per data attribute, collectively forming a weight vector. The score of an option (data record) is defined as the weighted sum of its individual attributes. The highest-scoring options across a set of alternatives (dataset) are shortlisted for the user as the recommended ones. In that setting, the user input is a vector (equivalently, a point) in a d-dimensional preference space, where d is the number of data attributes. In this paper we study the problem of determining in which regions of the preference space the weight vector should …
Provably Secure Attribute Based Signcryption With Delegated Computation And Efficient Key Updating,
2017
Nanjing University of Posts and Telecommunications
Provably Secure Attribute Based Signcryption With Delegated Computation And Efficient Key Updating, Hanshu Hong, Yunhao Xia, Zhixin Sun, Ximeng Liu
Research Collection School Of Computing and Information Systems
Equipped with the advantages of flexible access control and fine-grained authentication, attribute based signcryption is diffusely designed for security preservation in many scenarios. However, realizing efficient key evolution and reducing the calculation costs are two challenges which should be given full consideration in attribute based cryptosystem. In this paper, we present a key-policy attribute based signcryption scheme (KP-ABSC) with delegated computation and efficient key updating. In our scheme, an access structure is embedded into user’s private key, while ciphertexts corresponds a target attribute set. Only the two are matched can a user decrypt and verify the ciphertexts. When the access …
