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Articles 5491 - 5520 of 9024

Full-Text Articles in Computer Sciences

Event Detection With Zero Example: Select The Right And Suppress The Wrong Concepts, Yi-Jie Lu, Hao Zhang, Maaike De Boer, Chong-Wah Ngo Jun 2016

Event Detection With Zero Example: Select The Right And Suppress The Wrong Concepts, Yi-Jie Lu, Hao Zhang, Maaike De Boer, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Complex video event detection without visual examples is a very challenging issue in multimedia retrieval. We present a state-of-the-art framework for event search without any need of exemplar videos and textual metadata in search corpus. To perform event search given only query words, the core of our framework is a large, pre-built bank of concept detectors which can understand the content of a video in the perspective of object, scene, action and activity concepts. Leveraging such knowledge can effectively narrow the semantic gap between textual query and the visual content of videos. Besides the large concept bank, this paper focuses …

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How Long Will This Live? Discovering The Lifespans Of Software Engineering Ideas, Subhajit Datta, Santonu Sarkar, A. S. M Sajeev Jun 2016

How Long Will This Live? Discovering The Lifespans Of Software Engineering Ideas, Subhajit Datta, Santonu Sarkar, A. S. M Sajeev

Research Collection School Of Computing and Information Systems

We all want to be associated with long lasting ideas; as originators, or at least, expositors. For a tyro researcher or a seasoned veteran, knowing how long an idea will remain interesting in the community is critical in choosing and pursuing research threads. In the physical sciences, the notion of half-life is often evoked to quantify decaying intensity. In this paper, we study a corpus of 19,000+ papers written by 21,000+ authors across 16 software engineering publication venues from 1975 to 2010, to empirically determine the half-life of software engineering research topics. In the absence of any consistent and well-accepted …

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Serendipity-Driven Celebrity Video Hyperlinking, Shujun Yang, Lei Pang, Chong-Wah Ngo, Benoit Huet Jun 2016

Serendipity-Driven Celebrity Video Hyperlinking, Shujun Yang, Lei Pang, Chong-Wah Ngo, Benoit Huet

Research Collection School Of Computing and Information Systems

This demo showcases the utility of video hyperlinks with celebrities as the link anchors and their social circles as targets, aiming to help users quickly explore the aboutness of a celebrity by link traversal. Through content analysis, our system embeds hyperlinks into videos such that users can click-and-jump between celebrity faces in different videos to get-to-know their social circles. One peculiar feature is the ability of the system in providing links that maximize users' chance encounter, or serendipitous experience, beyond information need. Our system is enabled by two key components, name-face association and diversity-based ranking, for the aboutness and serendipity …

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Video Modeling And Learning On Riemannian Manifold For Emotion Recognition In The Wild, Mengyi Liu, Ruiping Wang, Shaoxin Li, Zhiwu Huang, Shiguang Shan, Xilin Chen Jun 2016

Video Modeling And Learning On Riemannian Manifold For Emotion Recognition In The Wild, Mengyi Liu, Ruiping Wang, Shaoxin Li, Zhiwu Huang, Shiguang Shan, Xilin Chen

Research Collection School Of Computing and Information Systems

In this paper, we present the method for our submission to the emotion recognition in the wild challenge (EmotiW). The challenge is to automatically classify the emotions acted by human subjects in video clips under real-world environment. In our method, each video clip can be represented by three types of image set models (i.e. linear subspace, covariance matrix, and Gaussian distribution) respectively, which can all be viewed as points residing on some Riemannian manifolds. Then different Riemannian kernels are employed on these set models correspondingly for similarity/ distance measurement. For classification, three types of classifiers, i.e. kernel SVM, logistic regression, …

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(Deterministic) Hierarchical Identity-Based Encryption From Learning With Rounding Over Small Modulus, Fuyang Fang, Bao Li, Xianhui Lu, Yamin Liu, Dingding Jia, Haiyang Xue Jun 2016

(Deterministic) Hierarchical Identity-Based Encryption From Learning With Rounding Over Small Modulus, Fuyang Fang, Bao Li, Xianhui Lu, Yamin Liu, Dingding Jia, Haiyang Xue

Research Collection School Of Computing and Information Systems

In this paper, we propose a hierarchical identity-based encryption (HIBE) scheme in the random oracle (RO) model based on the learning with rounding (LWR) problem over small modulus $q$. Compared with the previous HIBE schemes based on the learning with errors (LWE) problem, the ciphertext expansion ratio of our scheme can be decreased to 1/2. Then, we utilize the HIBE scheme to construct a deterministic hierarchical identity-based encryption (D-HIBE) scheme based on the LWR problem over small modulus. Finally, with the technique of binary tree encryption (BTE) we can construct HIBE and D-HIBE schemes in the standard model based on …

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Qcri At Semeval-2016 Task 4: Probabilistic Methods For Binary And Ordinal Quantification, Giovanni Da San Martino, Wei Gao, Fabrizio Sebastiani Jun 2016

Qcri At Semeval-2016 Task 4: Probabilistic Methods For Binary And Ordinal Quantification, Giovanni Da San Martino, Wei Gao, Fabrizio Sebastiani

Research Collection School Of Computing and Information Systems

. (2016). n. In , pages 58—63, San Diego, California, USA. Association for Computational Linguistics. (1st place in sub-task E of Sentiment Analysis in Twitter)

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Protecting The Nectar Of The Ganga River Through Game-Theoretic Factory Inspections, Benjamin Ford, Matthew Brown, Amulya Yadav, Amandeep Singh, Arunesh Sinha, Biplav Srivastava, Christopher Kiekintveld, Tambe Millind Jun 2016

Protecting The Nectar Of The Ganga River Through Game-Theoretic Factory Inspections, Benjamin Ford, Matthew Brown, Amulya Yadav, Amandeep Singh, Arunesh Sinha, Biplav Srivastava, Christopher Kiekintveld, Tambe Millind

Research Collection School Of Computing and Information Systems

Leather is an integral part of the world economy and a substantial income source for developing countries. Despite government regulations on leather tannery waste emissions, inspection agencies lack adequate enforcement resources, and tanneries’ toxic wastewaters wreak havoc on surrounding ecosystems and communities. Previous works in this domain stop short of generating executable solutions for inspection agencies. We introduce NECTAR - the first security game application to generate environmental compliance inspection schedules. NECTAR’s game model addresses many important real-world constraints: a lack of defender resources is alleviated via a secondary inspection type; imperfect inspections are modeled via a heterogeneous failure rate; …

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Recipient Revocable Identity-Based Broadcast Encryption: How To Revoke Some Recipients In Ibbe Without Knowledge Of The Plaintext, Willy Susilo, Guomin Yang, Rongmao Chen, Yi Mu, Fuchun Guo, Yang-Wai Chow Jun 2016

Recipient Revocable Identity-Based Broadcast Encryption: How To Revoke Some Recipients In Ibbe Without Knowledge Of The Plaintext, Willy Susilo, Guomin Yang, Rongmao Chen, Yi Mu, Fuchun Guo, Yang-Wai Chow

Research Collection School Of Computing and Information Systems

In this paper, we present the notion of recipient-revocable identity-based broadcast encryption scheme. In this notion, a content provider will produce encrypted content and send them to a third party (which is a broadcaster). This third party will be able to revoke some identities from the ciphertext. We present a security model to capture these requirements, as well as a concrete construction. The ciphertext consists of k + 3 group elements, assuming that the maximum number of revocation identities is k. That is, the ciphertext size is linear in the maximal size of R, where R is the revocation identity …

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Finding The Shortest Path In Stochastic Vehicle Routing: A Cardinality Minimization Approach, Zhiguang Cao, Hongliang Guo, Jie Zhang, Dusit Niyato, Ulrich Fastenrath Fastenrath Jun 2016

Finding The Shortest Path In Stochastic Vehicle Routing: A Cardinality Minimization Approach, Zhiguang Cao, Hongliang Guo, Jie Zhang, Dusit Niyato, Ulrich Fastenrath Fastenrath

Research Collection School Of Computing and Information Systems

This paper aims at solving the stochastic shortest path problem in vehicle routing, the objective of which is to determine an optimal path that maximizes the probability of arriving at the destination before a given deadline. To solve this problem, we propose a data-driven approach, which directly explores the big data generated in traffic. Specifically, we first reformulate the original shortest path problem as a cardinality minimization problem directly based on samples of travel time on each road link, which can be obtained from the GPS trajectory of vehicles. Then, we apply an l(1)-norm minimization technique and its variants to …

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Exemplar-Driven Top-Down Saliency Detection Via Deep Association, Shengfeng He, Rynson W. H. Lau, Qingxiong Yang Jun 2016

Exemplar-Driven Top-Down Saliency Detection Via Deep Association, Shengfeng He, Rynson W. H. Lau, Qingxiong Yang

Research Collection School Of Computing and Information Systems

Top-down saliency detection is a knowledge-driven search task. While some previous methods aim to learn this "knowledge" from category-specific data, others transfer existing annotations in a large dataset through appearance matching. In contrast, we propose in this paper a locateby-exemplar strategy. This approach is challenging, as we only use a few exemplars (up to 4) and the appearances among the query object and the exemplars can be very different. To address it, we design a two-stage deep model to learn the intra-class association between the exemplars and query objects. The first stage is for learning object-to-object association, and the second …

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The Frustrations And Benefits Of Mobile Device Usage In The Home When Co-Present With Family Members, Erick Oduor, Carman Neustaedter, William Odom, Anthony Tang, Niala Moallem, Melanie Tory, Pourang Irani Jun 2016

The Frustrations And Benefits Of Mobile Device Usage In The Home When Co-Present With Family Members, Erick Oduor, Carman Neustaedter, William Odom, Anthony Tang, Niala Moallem, Melanie Tory, Pourang Irani

Research Collection School Of Computing and Information Systems

Mobile devices have begun to raise questions around the potential for overuse when in the presence of family or friends. As such, we conducted a diary and interview study to understand how people use mobile devices in the presence of others at home, and how this shapes their behavior and household dynamics. Results show that family members become frustrated when others do non-urgent activities on their phones in the presence of others. Yet people often guess at what others are doing because of the personal nature of mobile devices. In some cases, people developed strategies to provide a greater sense …

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Deduplication On Encrypted Big Data In Cloud, Zheng Yan, Wenxiu Ding, Xixun Yu, Haiqi Zhu, Deng, Robert H. Jun 2016

Deduplication On Encrypted Big Data In Cloud, Zheng Yan, Wenxiu Ding, Xixun Yu, Haiqi Zhu, Deng, Robert H.

Research Collection School Of Computing and Information Systems

Cloud computing offers a new way of service provision by re-arranging various resources over the Internet. The most important and popular cloud service is data storage. In order to preserve the privacy of data holders, data are often stored in cloud in an encrypted form. However, encrypted data introduce new challenges for cloud data deduplication, which becomes crucial for big data storage and processing in cloud. Traditional deduplication schemes cannot work on encrypted data. Existing solutions of encrypted data deduplication suffer from security weakness. They cannot flexibly support data access control and revocation. Therefore, few of them can be readily …

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Poster: A Device-Free Evaluation System For Gymnastics Using Passive Rfid Tags, Binbin Xie, Jie Xiong, Dingyi Fang, Xiaojiang Chen, Anwen Wang, Zhanyong Tang Jun 2016

Poster: A Device-Free Evaluation System For Gymnastics Using Passive Rfid Tags, Binbin Xie, Jie Xiong, Dingyi Fang, Xiaojiang Chen, Anwen Wang, Zhanyong Tang

Research Collection School Of Computing and Information Systems

No abstract provided.

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Poster: Sonicnect: Accurate Hands-Free Gesture Input System With Smart Acoustic Sensing, Maotian Chang, Ping Li, Panlong Yang, Jie Xiong, Chang Tian Jun 2016

Poster: Sonicnect: Accurate Hands-Free Gesture Input System With Smart Acoustic Sensing, Maotian Chang, Ping Li, Panlong Yang, Jie Xiong, Chang Tian

Research Collection School Of Computing and Information Systems

This work presents Sonicnect, an acoustic sensing system with smartphone that enables accurate hands-free gesture input. Sonicnect leverages the embedded microphone in the smartphone to capture the subtle audio signals generated with fingers touching on the table. It supports 9 commonly used gestures (click, flip, scroll and zoom, etc) with above 92% recognition accuracy, and the minimum gesture movement could be 2cm. Distinguishable features are then extracted by exploiting spatio-temporal and frequency properties of the subtle audio signals. We conduct extensive real environment experiments to evaluate its performance. The results validate the effectiveness and robustness of Sonicnect.

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Dual Formulations For Optimizing Dec-Pomdp Controllers, Akshat Kumar, Hala Mostafa, Shlomo Zilberstein Jun 2016

Dual Formulations For Optimizing Dec-Pomdp Controllers, Akshat Kumar, Hala Mostafa, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

Decentralized POMDP is an expressive model for multi-agent planning. Finite-state controllers (FSCs)---often used to represent policies for infinite-horizon problems---offer a compact, simple-to-execute policy representation. We exploit novel connections between optimizing decentralized FSCs and the dual linear program for MDPs. Consequently, we describe a dual mixed integer linear program (MIP) for optimizing deterministic FSCs. We exploit the Dec-POMDP structure to devise a compact MIP and formulate constraints that result in policies executable in partially-observable decentralized settings. We show analytically that the dual formulation can also be exploited within the expectation maximization (EM) framework to optimize stochastic FSCs. The resulting EM algorithm …

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Self-Organizing Neural Network For Adaptive Operator Selection In Evolutionary Search, Teck Hou Teng, Stephanus Daniel Handoko, Hoong Chuin Lau Jun 2016

Self-Organizing Neural Network For Adaptive Operator Selection In Evolutionary Search, Teck Hou Teng, Stephanus Daniel Handoko, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Evolutionary Algorithm is a well-known meta-heuristics paradigm capable of providing high-quality solutions to computationally hard problems. As with the other meta-heuristics, its performance is often attributed to appropriate design choices such as the choice of crossover operators and some other parameters. In this chapter, we propose a continuous state Markov Decision Process model to select crossover operators based on the states during evolutionary search. We propose to find the operator selection policy efficiently using a self-organizing neural network, which is trained offline using randomly selected training samples. The trained neural network is then verified on test instances not used for …

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Geometric Aspects And Auxiliary Features To Top-K Processing [Advanced Seminar], Kyriakos Mouratidis Jun 2016

Geometric Aspects And Auxiliary Features To Top-K Processing [Advanced Seminar], Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

Top-k processing is a well-studied problem with numerous applications that is becoming increasingly relevant with the growing availability of recommendation systems and decision making software on PCs, PDAs and smart-phones. The objective of this seminar is twofold. First, we will delve into the geometric aspects of top-k processing. Second, we will cover complementary features to top-k queries that have a strong geometric nature. The seminar will close with insights in the effect of dimensionality on the meaningfulness of top-k queries, and interesting similarities to nearest neighbor search.

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An Experimental Investigation Of Product Competition And Marketing In Social Networks, Cen Chen, Zhiling Guo, Shih-Fen Cheng, Hoong Chuin Lau Jun 2016

An Experimental Investigation Of Product Competition And Marketing In Social Networks, Cen Chen, Zhiling Guo, Shih-Fen Cheng, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We conduct computational experiment using Facebook data to evaluate competing firms’ initial market seeding and subsequent targeted marketing strategies that influence consumers’ new product adoption decisions. We find that firms generally overspend their advertising budget in the market seeding phase. In the subsequent market advertising phase, a coupon strategy (equivalent to price discount) generally yields higher market share than the strategy of distributing free product samples. The effect is more significant when both price and product quality are low. We offer managerial insights into firms’ effective competition strategies for new product introduction in the presence of consumers’ word of mouth …

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An Economic Analysis Of Consumer Learning For Online Entertainment Shopping, Jin Li, Zhiling Guo, Geoffrey K.F. Tso Jun 2016

An Economic Analysis Of Consumer Learning For Online Entertainment Shopping, Jin Li, Zhiling Guo, Geoffrey K.F. Tso

Research Collection School Of Computing and Information Systems

Entertainment shopping supported by pay-to-bid auction is an emerging online business model in recent years. Consumers expect both entertainment value and monetary return from their participation in entertainment shopping. We propose a dynamic structural model to study consumers’ online shopping behavior. We analyze the learning process of consumers from two perspectives based on the Bayesian updating framework: (1) consumers update their beliefs about the entertainment value through their repeated personal participation experiences, and (2) consumers infer the expected monetary payoffs on the website by observing the publically available auction ending price information. We estimate the model using a large dataset …

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Learning Natural Language Inference With Lstm, Shuohang Wang, Jing Jiang Jun 2016

Learning Natural Language Inference With Lstm, Shuohang Wang, Jing Jiang

Research Collection School Of Computing and Information Systems

Natural language inference (NLI) is a fundamentally important task in natural language processing that has many applications. The recently released Stanford Natural Language Inference (SNLI) corpus has made it possible to develop and evaluate learning-centered methods such as deep neural networks for natural language inference (NLI). In this paper, we propose a special long short-term memory (LSTM) architecture for NLI. Our model builds on top of a recently proposed neural attention model for NLI but is based on a significantly different idea. Instead of deriving sentence embeddings for the premise and the hypothesis to be used for classification, our solution …

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Efficient Multi-Class Selective Sampling On Graphs, Peng Yang, Peilin Zhao, Zhen Hai, Wei Liu, Hoi, Steven C. H., Xiao-Li Li Jun 2016

Efficient Multi-Class Selective Sampling On Graphs, Peng Yang, Peilin Zhao, Zhen Hai, Wei Liu, Hoi, Steven C. H., Xiao-Li Li

Research Collection School Of Computing and Information Systems

A graph-based multi-class classification problem is typically converted into a collection of binary classification tasks via the one-vs.-all strategy, and then tackled by applying proper binary classification algorithms. Unlike the one-vs.-all strategy, we suggest a unified framework which operates directly on the multi-class problem without reducing it to a collection of binary tasks. Moreover, this framework makes active learning practically feasible for multi-class problems, while the one-vs.-all strategy cannot. Specifically, we employ a novel randomized query technique to prioritize the informative instances. This query technique based on the hybrid criterion of "margin" and "uncertainty" can achieve a comparable mistake bound …

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Demo: Wearable Application To Manage Problem Behavior In Children With Neurodevelopmental Disorders, Camellia Zakaria, Richard C. Davis Jun 2016

Demo: Wearable Application To Manage Problem Behavior In Children With Neurodevelopmental Disorders, Camellia Zakaria, Richard C. Davis

Research Collection School Of Computing and Information Systems

Managing problem behaviors in children with neurodevelopmental disorders can be challenging. Such behaviors may discourage social participation and learning. Many of these behaviors warrant intervention, however, are challenging for caregivers to constantly supervise. Previous work focused on developing recognition systems for stereotypical and aggressive behaviors. Researchers also developed visualization interface for caregivers to better understand their child’s needs. Our goal however, is to design an independent behavior management application to help children manage problem behaviors with minimal supervision.We conducted a field study at a school for children with special needs in Singapore, and interviewed ten teachers. This study helped us …

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Seeking Independent Management Of Problem Behavior: A Proof-Of-Concept Study With Children And Their Teachers, Camellia Zakaria, Richard C. Davis, Zachary Walker Jun 2016

Seeking Independent Management Of Problem Behavior: A Proof-Of-Concept Study With Children And Their Teachers, Camellia Zakaria, Richard C. Davis, Zachary Walker

Research Collection School Of Computing and Information Systems

Problem behaviors are particularly common in children with neurodevelopmental disorders like Autism and Down syndrome. These behaviors sometimes discourage social inclusion, inhibit learning development, and cause severe injuries, but caregivers are often unable to attend to their children immediately when the behaviors occur. Recent research shows that problem behavior can be automatically detected with wearable devices, but it is still not clear how to reduce caregivers' burdens and facilitate academic, social, and functional development of children with problem behaviors. We conducted a field study at a school with 21 children who exhibit problem behaviors and found that they needed frequent …

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Poster: Android Whole-System Control Flow Analysis For Accurate Application Behavior Modeling, Huu Hoang Nguyen Jun 2016

Poster: Android Whole-System Control Flow Analysis For Accurate Application Behavior Modeling, Huu Hoang Nguyen

Research Collection School Of Computing and Information Systems

Android, the modern operating system for smartphones, together with its millions of apps, has become an important part of human life. There are many challenges to analyzing them. It is important to model the mobile systems in order to analyze the behaviors of apps accurately. These apps are built on top of interactions with Android systems. We aim to automatically build abstract models of the mobile systems and thus automate the analysis of mobile applications and detect potential issues (e.g., leaking private data, causing unexpected crashes, etc.). The expected results will be the accuracy models of actual various versions of …

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Demo: Ta$Ker: Campus-Scale Mobile Crowd-Tasking Platform, Nikita Jaiman, Thivya Kandappu, Randy Tandriansyah, Archan Misra Jun 2016

Demo: Ta$Ker: Campus-Scale Mobile Crowd-Tasking Platform, Nikita Jaiman, Thivya Kandappu, Randy Tandriansyah, Archan Misra

Research Collection School Of Computing and Information Systems

We design and develop TA$Ker, a real-world mobile crowd- sourcing platform to empirically study the worker responses to various task recommendation and selection strategies.

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Condensing Class Diagrams With Minimal Manual Labeling Cost, Xinli Yang, David Lo, Xin Xia, Jianling Sun Jun 2016

Condensing Class Diagrams With Minimal Manual Labeling Cost, Xinli Yang, David Lo, Xin Xia, Jianling Sun

Research Collection School Of Computing and Information Systems

Traditionally, to better understand the design of a project, developers can reconstruct a class diagram from source code using a reverse engineering technique. However, the raw diagram is often perplexing because there are too many classes in it. Condensing the reverse engineered class diagram into a compact class diagram which contains only the important classes would enhance the understandability of the corresponding project. A number of recent works have proposed several supervised machine learning solutions that can be used for condensing reverse engineered class diagrams given a set of classes that are manually labeled as important or not. However, a …

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Automated Identification Of High Impact Bug Reports Leveraging Imbalanced Learning Strategies, Xinli Yang, David Lo, Qiao Huang, Xin Xia, Jianling Sun Jun 2016

Automated Identification Of High Impact Bug Reports Leveraging Imbalanced Learning Strategies, Xinli Yang, David Lo, Qiao Huang, Xin Xia, Jianling Sun

Research Collection School Of Computing and Information Systems

In practice, some bugs have more impact than others and thus deserve more immediate attention. Due to tight schedule and limited human resource, developers may not have enough time to inspect all bugs. Thus, they often concentrate on bugs that are highly impactful. In the literature, high impact bugs are used to refer to the bugs which appear in unexpected time or locations and bring more unexpected effects, or break pre-existing functionalities and destroy the user experience. Unfortunately, identifying high impact bugs from the thousands of bug reports in a bug tracking system is not an easy feat. Thus, an …

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Mobipot: Understanding Mobile Telephony Threats With Honeycards, Marco Balduzzi, Payas Gupta, Lion Gu, Debin Gao, Mustaque Ahamad Jun 2016

Mobipot: Understanding Mobile Telephony Threats With Honeycards, Marco Balduzzi, Payas Gupta, Lion Gu, Debin Gao, Mustaque Ahamad

Research Collection School Of Computing and Information Systems

Over the past decade, the number of mobile phones has increased dramatically, overtaking the world population in October 2014. In developing countries like India and China, mobile subscribers outnumber traditional landline users and account for over 90% of the active population. At the same time, convergence of telephony with the Internet with technologies like VoIP makes it possible to reach a large number of telephone users at a low or no cost via voice calls or SMS (short message service) messages. As a consequence, cybercriminals are abusing the telephony channel to launch attacks, e.g., scams that offer fraudulent services and …

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Cace: Exploiting Behavioral Interactions For Improved Activity Recognition In Multi-Inhabitant Smart Homes, Mohammad Arif Ul Alam, Nirmalya Roy, Archan Misra, Joseph Taylor Jun 2016

Cace: Exploiting Behavioral Interactions For Improved Activity Recognition In Multi-Inhabitant Smart Homes, Mohammad Arif Ul Alam, Nirmalya Roy, Archan Misra, Joseph Taylor

Research Collection School Of Computing and Information Systems

We propose CACE (Constraints And Correlations mining Engine) which investigates the challenges of improving the recognition of complex daily activities in multi-inhabitant smart homes, by better exploiting the spatiotemporal relationships across the activities of different individuals. We first propose and develop a loosely-coupled Hierarchical Dynamic Bayesian Network (HDBN), which both (a) captures the hierarchical inference of complex (macro-activity) contexts from lower-layer microactivity context (postural and improved oral gestural context), and (b) embeds the various types of behavioral correlations and constraints (at both micro-and macro-activity contexts) across the individuals. While this model is rich in terms of accuracy, it is computationally …

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Poster: Improving Communication And Communicability With Smarter Use Of Text-Based Messages On Mobile And Wearable Devices, Kenny T. W. Choo Jun 2016

Poster: Improving Communication And Communicability With Smarter Use Of Text-Based Messages On Mobile And Wearable Devices, Kenny T. W. Choo

Research Collection School Of Computing and Information Systems

While smartphones have undoubtedly afforded many modern conveniences such as emails, instant messaging or web search, the notifications from smartphones conversely impact our lives through a deluge of information, or stress arising from expectations that we should turn our immediate attention to them (e.g., work emails). In my latest research, we find that the glanceability of smartwatches may provide an opportunity to reduce the perceived disruption from mobile notifications. Text is a common medium for communication in smart devices, the application of natural language processing on text, together with the physical affordances of smartwatches, present exciting opportunities for research to …

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