Open Access. Powered by Scholars. Published by Universities.®

Physical Sciences and Mathematics Commons™

Open Access. Powered by Scholars. Published by Universities.®

Singapore Management University

Research Collection School Of Computing and Information Systems

2018

Articles 1 - 30 of 393

Full-Text Articles in Physical Sciences and Mathematics

Multi-Task Zipping Via Layer-Wise Neuron Sharing, Xiaoxi He, Zimu Zhou, Lothar Thiele Dec 2018

Multi-Task Zipping Via Layer-Wise Neuron Sharing, Xiaoxi He, Zimu Zhou, Lothar Thiele

Research Collection School Of Computing and Information Systems

Future mobile devices are anticipated to perceive, understand and react to the world on their own by running multiple correlated deep neural networks on-device. Yet the complexity of these neural networks needs to be trimmed down both within-model and cross-model to fit in mobile storage and memory. Previous studies squeeze the redundancy within a single model. In this work, we aim to reduce the redundancy across multiple models. We propose Multi-Task Zipping (MTZ), a framework to automatically merge correlated, pre-trained deep neural networks for cross-model compression. Central in MTZ is a layer-wise neuron sharing and incoming weight updating scheme that …

Go to article

Credit Assignment For Collective Multiagent Rl With Global Rewards, Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau Dec 2018

Credit Assignment For Collective Multiagent Rl With Global Rewards, Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Scaling decision theoretic planning to large multiagent systems is challenging due to uncertainty and partial observability in the environment. We focus on a multiagent planning model subclass, relevant to urban settings, where agent interactions are dependent on their collective influence'' on each other, rather than their identities. Unlike previous work, we address a general setting where system reward is not decomposable among agents. We develop collective actor-critic RL approaches for this setting, and address the problem of multiagent credit assignment, and computing low variance policy gradient estimates that result in faster convergence to high quality solutions. We also develop difference …

Go to article

Applying Design Thinking To Student Outreach Projects: Experiences From An Information Systems School, Swapna Gottipati, Venky Shankararaman, Alan Megargel Dec 2018

Applying Design Thinking To Student Outreach Projects: Experiences From An Information Systems School, Swapna Gottipati, Venky Shankararaman, Alan Megargel

Research Collection School Of Computing and Information Systems

As countries turn into Smart Nations, Infocom Technology plays a key role in enhancing their competitiveness through high skilled workforces. Reaching to younger generations and attracting them to computing programs such as Information Systems (IS) and Computer Science (CS) is a key challenge faced by universities. Many high quality students from junior colleges either don’t choose IS programs or choose IS programs as their last option during the application process. A School of Information Systems (SIS) from a large metropolitan university decided to implement an innovative outreach program to attract high quality high school aka Junior College (JC) students. JC …

Go to article

Sybmatch: Sybil Detection For Privacy-Preserving Task Matching In Crowdsourcing, Jiangang Shu, Ximeng Liu, Kan Yang, Yinghui Zhang, Xiaohua Jia, Robert H. Deng Dec 2018

Sybmatch: Sybil Detection For Privacy-Preserving Task Matching In Crowdsourcing, Jiangang Shu, Ximeng Liu, Kan Yang, Yinghui Zhang, Xiaohua Jia, Robert H. Deng

Research Collection School Of Computing and Information Systems

The past decade has witnessed the rise of crowdsourcing, and privacy in crowdsourcing has also gained rising concern in the meantime. In this paper, we focus on the privacy leaks and sybil attacks during the task matching, and propose a privacy-preserving task matching scheme, called SybMatch. The SybMatch scheme can simultaneously protect the privacy of publishers and subscribers against semi-honest crowdsourcing service provider, and meanwhile support the sybil detection against greedy subscribers and efficient user revocation. Detailed security analysis and thorough performance evaluation show that the SybMatch scheme is secure and efficient.

Go to article

A Simple Proximal Stochastic Gradient Method For Nonsmooth Nonconvex Optimization, Zhize Li, Jian Li Dec 2018

A Simple Proximal Stochastic Gradient Method For Nonsmooth Nonconvex Optimization, Zhize Li, Jian Li

Research Collection School Of Computing and Information Systems

We analyze stochastic gradient algorithms for optimizing nonconvex, nonsmooth finite-sum problems. In particular, the objective function is given by the summation of a differentiable (possibly nonconvex) component, together with a possibly non-differentiable but convex component. We propose a proximal stochastic gradient algorithm based on variance reduction, called ProxSVRG+. Our main contribution lies in the analysis of ProxSVRG+. It recovers several existing convergence results and improves/generalizes them (in terms of the number of stochastic gradient oracle calls and proximal oracle calls). In particular, ProxSVRG+ generalizes the best results given by the SCSG algorithm, recently proposed by [Lei et al., NIPS'17] for …

Go to article

Using Smart Card Data To Model Commuters’ Responses Upon Unexpected Train Delays, Xiancai Tian, Baihua Zheng Dec 2018

Using Smart Card Data To Model Commuters’ Responses Upon Unexpected Train Delays, Xiancai Tian, Baihua Zheng

Research Collection School Of Computing and Information Systems

The mass rapid transit (MRT) network is playing an increasingly important role in Singapore's transit network, thanks to its advantages of higher capacity and faster speed. Unfortunately, due to aging infrastructure, increasing demand, and other reasons like adverse weather condition, commuters in Singapore recently have been facing increasing unexpected train delays (UTDs), which has become a source of frustration for both commuters and operators. Most, if not all, existing works on delay management do not consider commuters' behavior. We dedicate this paper to the study of commuters' behavior during UTDs. We adopt a data-driven approach to analyzing the six-month' real …

Go to article

An Economic Analysis Of Incentivized Positive Reviews, Jianqing Chen, Zhiling Guo, Jian Huang Dec 2018

An Economic Analysis Of Incentivized Positive Reviews, Jianqing Chen, Zhiling Guo, Jian Huang

Research Collection School Of Computing and Information Systems

It becomes increasingly popular that some large online retailers such as Amazon open their platforms to allow third-party retail competitors to sell on their own platforms. We develop an analytical model to examine this retailer marketplace model and its business impact. We assume that a leading retailer has both valuation advantage that may come from its reputation and information advantage that may come from its brand awareness. We find that the availability of relatively low-cost advertising through social media or search engine can effectively reduce the leading retailer's information advantage, and thus be an important driving force for its strategic …

Go to article

Secure Smart Health With Privacy-Aware Aggregate Authentication And Access Control In Internet Of Things, Yinghui Zhang, Robert H. Deng, Gang Han, Dong Zheng Dec 2018

Secure Smart Health With Privacy-Aware Aggregate Authentication And Access Control In Internet Of Things, Yinghui Zhang, Robert H. Deng, Gang Han, Dong Zheng

Research Collection School Of Computing and Information Systems

With the rapid technological advancements in the Internet of Things (IoT), wireless communication and cloud computing, smart health is expected to enable comprehensive and qualified healthcare services. It is important to ensure security and efficiency in smart health. However, existing smart health systems still have challenging issues, such as aggregate authentication, fine-grained access control and privacy protection. In this paper, we address these issues by introducing SSH, a Secure Smart Health system with privacy-aware aggregate authentication and access control in IoT. In SSH, privacy-aware aggregate authentication is enabled by an anonymous certificateless aggregate signature scheme, in which users' identity information …

Go to article

Utilizing Computational Trust To Identify Rumor Spreaders On Twitter, Bhavtosh Rath, Wei Gao, Jing Ma, Jaideep Srivastava Dec 2018

Utilizing Computational Trust To Identify Rumor Spreaders On Twitter, Bhavtosh Rath, Wei Gao, Jing Ma, Jaideep Srivastava

Research Collection School Of Computing and Information Systems

Ubiquitous use of social media such as microblogging platforms opens unprecedented chances for false information to diffuse online. Facing the challenges in such a so-called “post-fact” era, it is very important for intelligent systems to not only check the veracity of information but also verify the authenticity of the users who spread the information, especially in time-critical situations such as real-world emergencies, where urgent measures have to be taken for stopping the spread of fake information. In this work, we propose a novel machine-learning-based approach for automatic identification of the users who spread rumorous information on Twitter by leveraging computational …

Go to article

Text Analytics Approach To Extract Course Improvement Suggestions From Students’ Feedback, Swapna Gottipati, Venky Shankararaman, Jeff Rongsheng Lin Dec 2018

Text Analytics Approach To Extract Course Improvement Suggestions From Students’ Feedback, Swapna Gottipati, Venky Shankararaman, Jeff Rongsheng Lin

Research Collection School Of Computing and Information Systems

In academic institutions, it is normal practice that at the end of each term, students are required to complete a questionnaire that is designed to gather students’ perceptions of the instructor and their learning experience in the course. Students’ feedback includes numerical answers to Likert scale questions and textual comments to open-ended questions. Within the textual comments given by the students are embedded suggestions. A suggestion can be explicit or implicit. Any suggestion provides useful pointers on how the instructor can further enhance the student learning experience. However, it is tedious to manually go through all the qualitative comments and …

Go to article

An Essential Applied Statistical Analysis Course Using Rstudio With Project-Based Learning For Data Science, Aldy Gunawan, Michelle L. F. Cheong, Johnson Poh Dec 2018

An Essential Applied Statistical Analysis Course Using Rstudio With Project-Based Learning For Data Science, Aldy Gunawan, Michelle L. F. Cheong, Johnson Poh

Research Collection School Of Computing and Information Systems

This paper presents a newpostgraduate level course, named Applied Statistical Analysis with R. Wepresent the course structure, teaching methodology including the assessmentframework and student feedback. The course covers the basic concepts ofstatistics, the knowledge of applying statistical theory in analyzing real dataand the skill of developing statistical applications with R programminglanguage. The first half of each lesson is dedicated to teaching students thestatistical concepts while the second half focuses on the practical aspects ofimplementing the concepts within the RStudio console. The Project-BasedLearning (PBL) approach is adopted to encourage students to apply the knowledgegained to solve real world problems, answer complex …

Go to article

Fogfly: A Traffic Light Optimization Solution Based On Fog Computing, Quang Tran Minh, Chanh Minh Tran, Tuan An Le, Binh Thai Nguyen, Triet Minh Tran, Rajesh Krishna Balan Dec 2018

Fogfly: A Traffic Light Optimization Solution Based On Fog Computing, Quang Tran Minh, Chanh Minh Tran, Tuan An Le, Binh Thai Nguyen, Triet Minh Tran, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

This paper provides a fog-based approach to solving the traffic light optimization problem which utilizes the Adaptive Traffic Signal Control (ATSC) model. ATSC systems demand the ability to strictly reflect real-time traffic state. The proposed fog computing framework, namely FogFly, aligns with this requirement by its natures in location-awareness, low latency and affordability to the changes in traffic conditions. As traffic data is updated timely and processed at fog nodes deployed close to data sources (i.e., vehicles at intersections) traffic light cycles can be optimized efficiently while virtualized resources available at network edges are efficiently utilized. Evaluation results show that …

Go to article

An Architectural Design And Evaluation Of An Affective Tutoring System For Novice Programmers, Hua Leong Fwa Dec 2018

An Architectural Design And Evaluation Of An Affective Tutoring System For Novice Programmers, Hua Leong Fwa

Research Collection School Of Computing and Information Systems

Affect is prevalent in learning and it influences students’ learning achievement. This paper details the design and evaluation of an Affective Tutoring System (ATS) that tutors student in computer programming. Although most ATSs are purpose built for a specific domain, making adaptation to another domain difficult, this ATS is architected for adaptability and extensibility. This study also addresses a lack of research exploring the theories and methods of integrating affect and learning within the learning process by proposing methods of regulating the negative affect of students. Both quantitative and qualitative techniques were used for evaluation of the effectiveness of the …

Go to article

On Learning Psycholinguistics Tools For English-Based Creole Languages Using Social Media Data, Pei-Chi Lo, Ee-Peng Lim Dec 2018

On Learning Psycholinguistics Tools For English-Based Creole Languages Using Social Media Data, Pei-Chi Lo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

The Linguistic Inquiry and Word Count (LIWC) tool is a psycholinguistics tool that has been widely used in both psychology and sociology research, and the LIWC scores derived from user-generated content are known to be good features for personality prediction [1], [2]. LIWC, however, is language specific as it relies on counting the percentage of predefined dictionary words occurring in the content. For content written in English Creoles which are languages based on English, the original English LIWC may not perform optimally due to its lack of words which are only used in the English Creoles. In this paper, we …

Go to article

A Cloud-Based Data Gathering And Processing System For Intelligent Demand Forecasting, Colin K. L. Tay, Kyong Jin Shim Dec 2018

A Cloud-Based Data Gathering And Processing System For Intelligent Demand Forecasting, Colin K. L. Tay, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

Demand forecasting has been a challenging problem especially for products with short life cycles such as electronic goods and fashion items. Additionally, in the presence of limited past or historical data as well as the need for fast turnaround for forecast, producing timely and accurate demand forecast can be extremely challenging. In this study, we describe a cloud-based data gathering and processing system for intelligent demand forecasting.

Go to article

Early Prediction Of Merged Code Changes To Prioritize Reviewing Tasks, Yuanrui Fan, Xin Xia, David Lo, Shanping Li Dec 2018

Early Prediction Of Merged Code Changes To Prioritize Reviewing Tasks, Yuanrui Fan, Xin Xia, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Modern Code Review (MCR) has been widely used by open source and proprietary software projects. Inspecting code changes consumes reviewers much time and effort since they need to comprehend patches, and many reviewers are often assigned to review many code changes. Note that a code change might be eventually abandoned, which causes waste of time and effort. Thus, a tool that predicts early on whether a code change will be merged can help developers prioritize changes to inspect, accomplish more things given tight schedule, and not waste reviewing effort on low quality changes. In this paper, motivated by the above …

Go to article

Integrating Node Embeddings And Biological Annotations For Genes To Predict Disease-Gene Associations, Sezin Kircali Ata, Le Ou-Yang, Yuan Fang, Chee-Keong Kwoh, Min Wu, Xiao-Li Li Dec 2018

Integrating Node Embeddings And Biological Annotations For Genes To Predict Disease-Gene Associations, Sezin Kircali Ata, Le Ou-Yang, Yuan Fang, Chee-Keong Kwoh, Min Wu, Xiao-Li Li

Research Collection School Of Computing and Information Systems

Background: Predicting disease causative genes (or simply, disease genes) has played critical roles in understandingthe genetic basis of human diseases and further providing disease treatment guidelines. While various computationalmethods have been proposed for disease gene prediction, with the recent increasing availability of biologicalinformation for genes, it is highly motivated to leverage these valuable data sources and extract useful information foraccurately predicting disease genes. Results: We present an integrative framework called N2VKO to predict disease genes. Firstly, we learn the nodeembeddings from protein-protein interaction (PPI) network for genes by adapting the well-known representationlearning method node2vec. Secondly, we combine the learned node …

Go to article

Data Mining Approach To The Detection Of Suicide In Social Media: A Case Study Of Singapore, Jane H. K. Seah, Kyong Jin Shim Dec 2018

Data Mining Approach To The Detection Of Suicide In Social Media: A Case Study Of Singapore, Jane H. K. Seah, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

In this research, we focus on the social phenomenon of suicide. Specifically, we perform social sensing on digital traces obtained from Reddit. We analyze the posts and comments in that are related to depression and suicide. We perform natural language processing to better understand different aspects of human life that relate to suicide.

Go to article

Making A Good Thing Better: Enhancing Password/Pin-Based User Authentication With Smartwatch, Bing Chang, Yingjiu Li, Qiongxiao Wang, Wen-Tao Zhu, Robert H. Deng Dec 2018

Making A Good Thing Better: Enhancing Password/Pin-Based User Authentication With Smartwatch, Bing Chang, Yingjiu Li, Qiongxiao Wang, Wen-Tao Zhu, Robert H. Deng

Research Collection School Of Computing and Information Systems

Wearing smartwatches becomes increasingly popular in people’s lives. This paper shows that a smartwatch can help its bearer authenticate to a login system effectively and securely even if the bearer’s password has already been revealed. This idea is motivated by our observation that a sensor-rich smartwatch is capable of tracking the wrist motions of its bearer typing a password or PIN, which can be used as an authentication factor. The major challenge in this research is that a sophisticated attacker may imitate a user’s typing behavior as shown in previous research on keystroke dynamics based user authentication. We address this …

Go to article

Typing-Proof: Usable, Secure And Low-Cost Two-Factor Authentication Based On Keystroke Timings, Ximming Liu, Yingjiu Li, Robert H. Deng Dec 2018

Typing-Proof: Usable, Secure And Low-Cost Two-Factor Authentication Based On Keystroke Timings, Ximming Liu, Yingjiu Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

Two-factor authentication (2FA) systems provide another layer of protection to users' accounts beyond password. Traditional hardware token based 2FA and software token based 2FA are not burdenless to users since they require users to read, remember, and type a onetime code in the process, and incur high costs in deployments or operations. Recent 2FA mechanisms such as Sound-Proof, reduce or eliminate users' interactions for the proof of the second factor; however, they are not designed to be used in certain settings (e.g., quiet environments or PCs without built-in microphones), and they are not secure in the presence of certain attacks …

Go to article

Mobility-Driven Ble Transmit-Power Adaptation For Participatory Data Muling, Chung-Kyun Han, Archan Misra, Shih-Fen Cheng Dec 2018

Mobility-Driven Ble Transmit-Power Adaptation For Participatory Data Muling, Chung-Kyun Han, Archan Misra, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

This paper analyzes a human-centric framework, called SmartABLE, for easy retrieval of the sensor values from pervasively deployed smart objects in a campus-like environment. In this framework, smartphones carried by campus occupants act as data mules, opportunistically retrieving data from nearby BLE (Bluetooth Low Energy) equipped smart object sensors and relaying them to a backend repository. We focus specifically on dynamically varying the transmission power of the deployed BLE beacons, so as to extend their operational lifetime without sacrificing the frequency of sensor data retrieval. We propose a memetic algorithm-based power adaptation strategy that can handle deployments of thousands of …

Go to article

Towards Mining Comprehensive Android Sandboxes, Tien-Duy B. Le, Lingfeng Bao, David Lo, Debin Gao, Li Li Dec 2018

Towards Mining Comprehensive Android Sandboxes, Tien-Duy B. Le, Lingfeng Bao, David Lo, Debin Gao, Li Li

Research Collection School Of Computing and Information Systems

Android is the most widely used mobile operating system with billions of users and devices. The popularity of Android apps have enticed malware writers to target them. Recently, Jamrozik et al. proposed an approach, named Boxmate, to mine sandboxes to protect Android users from malicious behaviors. In a nutshell, Boxmate analyzes the execution of an app, and collects a list of sensitive APIs that are invoked by that app in a monitoring phase. Then, it constructs a sandbox that can restrict accesses to sensitive APIs not called by the app. In such a way, malicious behaviors that are not observed …

Go to article

Perflearner: Learning From Bug Reports To Understand And Generate Performance Test Frames, Xue Han, Tingting Yu, David Lo Dec 2018

Perflearner: Learning From Bug Reports To Understand And Generate Performance Test Frames, Xue Han, Tingting Yu, David Lo

Research Collection School Of Computing and Information Systems

Software performance is important for ensuring the quality of software products. Performance bugs, defined as programming errors that cause significant performance degradation, can lead to slow systems and poor user experience. While there has been some research on automated performance testing such as test case generation, the main idea is to select workload values to increase the program execution times. These techniques often assume the initial test cases have the right combination of input parameters and focus on evolving values of certain input parameters. However, such an assumption may not hold for highly configurable real-word applications, in which the combinations …

Go to article

Better Inpatient Health Quality At Lower Cost: Should I Participate In The Online Healthcare Community First?, Kai Luo, Qiu-Hong Wang, Hock Hai Teo, Xi Chen Dec 2018

Better Inpatient Health Quality At Lower Cost: Should I Participate In The Online Healthcare Community First?, Kai Luo, Qiu-Hong Wang, Hock Hai Teo, Xi Chen

Research Collection School Of Computing and Information Systems

As policy makers across the globe look to health information technology (HIT) as a meansof improving the efficiency of the healthcare systems, it has sparked significant interestin understanding how HIT might help achieve that. While researchers have examined anddocumented the efficiency-improving effect of various institution HITs (e.g., electronicclinic pathways and telemedicine), the impacts of consumer HITs such as onlinehealthcare communities have been generally overlooked. Utilizing two unique datasetsfrom both an online healthcare community and a general hospital, we study the impactof online healthcare community on offline inpatient care efficiency. Through rigorousanalysis, we find that communications between physicians and patients on …

Go to article

Data Mining Approach To The Identification Of At-Risk Students, Li Chin Ho, Kyong Jin Shim Dec 2018

Data Mining Approach To The Identification Of At-Risk Students, Li Chin Ho, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

In recent years, the use of digital tools and technologies in educational institutions are continuing to generate large amounts of digital traces of student learning behavior. This study presents a proof-of-concept analytics system that can detect at-risk students along their learning journey. Educators can benefit from the early detection of at-risk students by understanding factors which may lead to failure or drop-out. Further, educators can devise appropriate intervention measures before the students drop out of the course. Our system was built using SAS ® Enterprise Miner (EM) and SAS ® JMP Pro.

Go to article

Privacy-Preserving Remote User Authentication With K-Times Untraceability, Yangguang Tian, Yingjiu Li, Binanda Sengupta, Robert H. Deng, Albert Ching, Weiwei Liu Dec 2018

Privacy-Preserving Remote User Authentication With K-Times Untraceability, Yangguang Tian, Yingjiu Li, Binanda Sengupta, Robert H. Deng, Albert Ching, Weiwei Liu

Research Collection School Of Computing and Information Systems

Remote user authentication has found numerous real-world applications, especially in a user-server model. In this work, we introduce the notion of anonymous remote user authentication with k-times untraceability (k-RUA) for a given parameter k, where authorized users authenticate themselves to an authority (typically a server) in an anonymous and k-times untraceable manner. We define the formal security models for a generic k-RUA construction that guarantees user authenticity, anonymity and user privacy. We provide a concrete instantiation of k-RUA having the following properties: (1) a third party cannot impersonate an authorized user by producing valid transcripts for the user while conversing …

Go to article

Integrated Reward Scheme And Surge Pricing In A Ride-Sourcing Market, Hai Yang, Chaoyi Shao, Hai Wang, Jieping Ye Dec 2018

Integrated Reward Scheme And Surge Pricing In A Ride-Sourcing Market, Hai Yang, Chaoyi Shao, Hai Wang, Jieping Ye

Research Collection School Of Computing and Information Systems

Surge pricing is commonly used in on-demand ride-sourcing platforms (e.g., Uber, Lyft and Didi) to dynamically balance demand and supply. However, since the price for ride service cannot be unlimited, there is usually a reasonable or legitimate range of prices in practice. Such a constrained surge pricing strategy fails to balance demand and supply in certain cases, e.g., even adopting the maximum allowed price cannot reduce the demand to an affordable level during peak hours. In addition, the practice of surge pricing is controversial and has stimulated long debate regarding its pros and cons. To address the limitation of current …

Go to article

Pribioauth: Privacy-Preserving Biometric-Based Remote User Authentication, Yangguang Tian, Yingjiu Li, Ximeng Liu, Robert H. Deng, Binanda Sengupta Dec 2018

Pribioauth: Privacy-Preserving Biometric-Based Remote User Authentication, Yangguang Tian, Yingjiu Li, Ximeng Liu, Robert H. Deng, Binanda Sengupta

Research Collection School Of Computing and Information Systems

Biometric-based remote user authentication (BRUA) is a useful primitive that allows an authorized user to remotely authenticate to a cloud server using biometrics. However, the existing BRUA solutions in the client-server setting lack certain privacy considerations. For example, authorized user's multiple sessions should not be linked while his identity remains anonymous to cloud server. In this work, we introduce an identity-concealed and unlinkable biometric-based remote user authentication framework, such that authorized users authenticate to an honest-but-curious server in an anonymous and unlinkable manner. In particular, we employ two non-colluding cloud servers to perform the complex biometrics matching. We formalize two …

Go to article

Attention-Based Lstm-Cnns For Uncertainty Identification On Chinese Social Media Texts, Binyang Li, Kaiming Zhou, Wei Gao, Xu Han Han, Linna Zhou Dec 2018

Attention-Based Lstm-Cnns For Uncertainty Identification On Chinese Social Media Texts, Binyang Li, Kaiming Zhou, Wei Gao, Xu Han Han, Linna Zhou

Research Collection School Of Computing and Information Systems

Uncertainty identification is an important semantic processing task, which is crucial to the quality of information in terms of factuality in many techniques, e.g. topic detection, question answering. Especially in social media, the texts are written informally which are widely used in many applications, so the factuality has become a premier concern. However, existing approaches that still rely on lexical cues suffer greatly from the casual or word-of-mouth peculiarity of social media, in which the cue phrases are often expressed in sub-standard form or even omitted from sentences. To tackle these problems, this paper proposes the attention-based LSTM-CNNs for the …

Go to article

Deep Air Learning: Interpolation, Prediction, And Feature Analysis Of Fine-Grained Air Quality, Zhongang Qi, Tianchun Wang, Guojie Song, Weisong Hu, Xi Li, Zhongfei Mark Zhang Dec 2018

Deep Air Learning: Interpolation, Prediction, And Feature Analysis Of Fine-Grained Air Quality, Zhongang Qi, Tianchun Wang, Guojie Song, Weisong Hu, Xi Li, Zhongfei Mark Zhang

Research Collection School Of Computing and Information Systems

The interpolation, prediction, and feature analysis of fine-gained air quality are three important topics in the area of urban air computing. The solutions to these topics can provide extremely useful information to support air pollution control, and consequently generate great societal and technical impacts. Most of the existing work solves the three problems separately by different models. In this paper, we propose a general and effective approach to solve the three problems in one model called the Deep Air Learning (DAL). The main idea of DAL lies in embedding feature selection and semi-supervised learning in different layers of the deep …

Go to article

Next Last