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Articles 2641 - 2670 of 4281
Full-Text Articles in Entire DC Network
Anonymous Proxy Signature With Hierarchical Traceability, Jiannan Wei, Guomin Yang, Yi Mu, Kaitai Liang
Anonymous Proxy Signature With Hierarchical Traceability, Jiannan Wei, Guomin Yang, Yi Mu, Kaitai Liang
Research Collection School Of Computing and Information Systems
Anonymous proxy signatures are very useful in the construction of anonymous credential systems such as anonymous voting and anonymous authentication protocols. As a basic requirement, we should ensure an honest proxy signer is anonymous. However, in order to prevent the proxy signer from abusing the signing right, we should also allow dishonest signers to be traced. In this paper, we present three novel anonymous proxy signature schemes with different levels of (namely, public, internal and original signer) traceability. We define the formal definitions and security models for these three different settings, and prove the security of our proposed schemes under …
Smokey: Ubiquitous Smoking Detection With Commercial Wifi Infrastructures, Xiaolong Zheng, Jiliang Wang, Longfei Shangguan, Zimu Zhou, Yunhao Liu
Smokey: Ubiquitous Smoking Detection With Commercial Wifi Infrastructures, Xiaolong Zheng, Jiliang Wang, Longfei Shangguan, Zimu Zhou, Yunhao Liu
Research Collection School Of Computing and Information Systems
Even though indoor smoking ban is being put into practice in civilized countries, existing vision or sensor-based smoking detection methods cannot provide ubiquitous smoking detection. In this paper, we take the first attempt to build a ubiquitous passive smoking detection system, which leverages the patterns smoking leaves on WiFi signals to identify the smoking activity even in the non-line-of-sight and through-wall environments. We study the behaviors of smokers and leverage the common features to recognize the series of motions during smoking, avoiding the target-dependent training set to achieve the high accuracy. We design a foreground detection based motion acquisition method …
Tuning By Turning: Enabling Phased Array Signal Processing For Wifi With Inertial Sensors, Kun Qian, Chenshu Wu, Zheng Yang, Zimu Zhou, Xu Wang, Yunhao Liu
Tuning By Turning: Enabling Phased Array Signal Processing For Wifi With Inertial Sensors, Kun Qian, Chenshu Wu, Zheng Yang, Zimu Zhou, Xu Wang, Yunhao Liu
Research Collection School Of Computing and Information Systems
Modern mobile devices are equipped with multiple antennas, which brings various wireless sensing applications such as accurate localization, contactless human detection and wireless human-device interaction. A key enabler for these applications is phased array signal processing, especially Angle of Arrival (AoA) estimation. However, accurate AoA estimation on commodity devices is non-trivial due to limited number of antennas and uncertain phase offsets. Previous works either rely on elaborate calibration or involve contrived human interactions. In this paper, we aim to enable practical AoA measurements on commodity off-the-shelf (COTS) mobile devices. The key insight is to involve users’ natural rotation to formulate …
Not You Too? Distilling Local Contexts Of Poor Cellular Network Performance Through Participatory Sensing, Huiguang Liang, Ido Nevat, Hyong S. Kim, Hwee-Pink Tan, Wai-Leong Yeow
Not You Too? Distilling Local Contexts Of Poor Cellular Network Performance Through Participatory Sensing, Huiguang Liang, Ido Nevat, Hyong S. Kim, Hwee-Pink Tan, Wai-Leong Yeow
Research Collection School Of Computing and Information Systems
Cellular service subscribers are increasingly reliant on cellular data services for all kinds of mobile applications. Oftentimes, when subscribers experience frustratingly high network delays and timeouts, they like to know whether their experiences are shared by other users nearby. The question that is often asked is essentially this: “is it just me, or do others around me face the same problem?” In this paper, we describe how we use Tattle, a distributed real-time participatory sensing and monitoring framework, to glean network performance information from users nearby. Tattle relies on recent advances in peer-to-peer device networking, such as Wi-Fi Direct, Bluetooth …
Ontology-Aided Feature Correlation For Multi-Modal Urban Sensing, Archan Misra, Zaman Lantra, Kasthuri Jayarajah
Ontology-Aided Feature Correlation For Multi-Modal Urban Sensing, Archan Misra, Zaman Lantra, Kasthuri Jayarajah
Research Collection School Of Computing and Information Systems
The paper explores the use of correlation across features extracted from different sensing channels to help in urban situational understanding. We use real-world datasets to show how such correlation can improve the accuracy of detection of city-wide events by combining metadata analysis with image analysis of Instagram content. We demonstrate this through a case study on the Singapore Haze. We show that simple ontological relationships and reasoning can significantly help in automating such correlation-based understanding of transient urban events.
Understanding The Determinants Of Human Computation Game Acceptance: The Effects Of Aesthetic Experience And Output Quality, Xiaohui Wang, Dion Hoe-Lian Goh, Ee-Peng Lim, Wei Liang Adrian Vu
Understanding The Determinants Of Human Computation Game Acceptance: The Effects Of Aesthetic Experience And Output Quality, Xiaohui Wang, Dion Hoe-Lian Goh, Ee-Peng Lim, Wei Liang Adrian Vu
Research Collection School Of Computing and Information Systems
Purpose: Human computation games (HCGs) that blend gaming with utilitarian purposes are a potentially effective channel for content creation. The purpose of this paper is to investigate the driving factors behind players’ adoption of HCGs through a music video tagging game. The effects of perceived aesthetic experience (PAE) and perceived output quality (POQ) on HCG acceptance are empirically examined. Design/methodology/approach: An integrative structural model is developed to explain how hedonic and utilitarian factors, including PAE and POQ, working with another salient factor – perceived usefulness (PU) – affect the acceptance of HCGs. The structural equation modeling method is used to …
Dual-Server Public-Key Encryption With Keyword Search For Secure Cloud Storage, Rongmao Chen, Yi Mu, Guomin Yang, Fuchun Guo, Xiaofen Wang
Dual-Server Public-Key Encryption With Keyword Search For Secure Cloud Storage, Rongmao Chen, Yi Mu, Guomin Yang, Fuchun Guo, Xiaofen Wang
Research Collection School Of Computing and Information Systems
Searchable encryption is of increasing interest for protecting the data privacy in secure searchable cloud storage. In this paper, we investigate the security of a well-known cryptographic primitive, namely, public key encryption with keyword search (PEKS) which is very useful in many applications of cloud storage. Unfortunately, it has been shown that the traditional PEKS framework suffers from an inherent insecurity called inside keyword guessing attack (KGA) launched by the malicious server. To address this security vulnerability, we propose a new PEKS framework named dual-server PEKS (DS-PEKS). As another main contribution, we define a new variant of the smooth projective …
Mercury Isotopes Of Atmospheric Particle Bound Mercury For Source Apportionment Study In Urban Kolkata, India, Reshmi Das, Xianfeng Wang, Bahareh Khezri, Richard D. Webster, Pradip Kumar Sikdar, Subhajit Datta
Mercury Isotopes Of Atmospheric Particle Bound Mercury For Source Apportionment Study In Urban Kolkata, India, Reshmi Das, Xianfeng Wang, Bahareh Khezri, Richard D. Webster, Pradip Kumar Sikdar, Subhajit Datta
Research Collection School Of Computing and Information Systems
The particle bound mercury (PBM) in urban-industrial areas is mainly of anthropogenic origin, and is derived from two principal sources: Hg bound to particulate matter directly emitted by industries and power generation plants, and adsorption of gaseous elemental mercury (GEM) and gaseous oxidized mercury (GOM) on air particulates from gas or aqueous phases. Here, we measured the Hg isotope composition of PBM in PM10 samples collected from three locations, a traffic junction, a waste incineration site and an industrial site in Kolkata, the largest metropolis in Eastern India. Sampling was carried out in winter and monsoon seasons between 2013–2015. …
Policy Analytics, Household Informedness And The Collection Of Household Hazardous Waste, Kustini Lim-Wavde, Robert J. Kauffman, Greg Dawson
Policy Analytics, Household Informedness And The Collection Of Household Hazardous Waste, Kustini Lim-Wavde, Robert J. Kauffman, Greg Dawson
Research Collection School Of Computing and Information Systems
Proper collection of Household Hazardous Waste (HHW) is an important action to support environmental sustainability. We investigate the role of household informedness, the degree to which households have the necessary information to make utility-maximizing decisions, as they relate to participation in HHW collection programs. We find two factors that influence household informedness: the provision of public education about HHW and environmental quality information. We conducted an empirical study on HHW collection in California to obtain statistical evidence on the effect of these factors on the amount of HHW collected. The findings of this policy analytics study improve our understanding of …
Where Am I? Characterizing And Improving The Localization Performance Of Off-The-Shelf Mobile Devices Through Cooperation, Huiguang Liang, Hyong S. Kim, Hwee-Pink Tan, Wai-Leong Yeow
Where Am I? Characterizing And Improving The Localization Performance Of Off-The-Shelf Mobile Devices Through Cooperation, Huiguang Liang, Hyong S. Kim, Hwee-Pink Tan, Wai-Leong Yeow
Research Collection School Of Computing and Information Systems
We are increasingly reliant on cellular data services for many types of day-to-day activities, from hailing a cab, to searching for nearby restaurants. Geo-location has become a ubiquitous feature that underpins the functionality of such applications. Network operators can also benefit from accurate mobile terminal localization in order to quickly detect and identify location-related network performance issues, such as coverage holes and congestion, based on mobile measurements. Current implementations of mobile localization on the wildly-popular Android platform depend on either the Global Positioning System (GPS), Android's Network Location Provider (NLP), or a combination of both. In this paper, we extensively …
Mycompetencies: Competency Tracking Mobile Application For Is Students, Gottipati Swapna, Shankararaman, Venky
Mycompetencies: Competency Tracking Mobile Application For Is Students, Gottipati Swapna, Shankararaman, Venky
Research Collection School Of Computing and Information Systems
The overall aim of learning outcomes and competency based education is to improve the efficiency and effectiveness of higher education. It's important to track regularly student's competency acquisition so that the faculty can improve the teaching delivery and adapt the content accordingly. Student based self-assessment of competency tracking on a weekly basis aids faculty to intervene in course delivery process for effective teaching and learning experience. It also helps students to have a better understanding of their competency levels and accordingly prepare for weekly sessions. To enable students to self-assess the competencies in more structured format, there is a need …
Large Scale Online Kernel Learning, Jing Lu, Hoi, Steven C. H., Jialei Wang, Peilin Zhao, Zhi-Yong Liu
Large Scale Online Kernel Learning, Jing Lu, Hoi, Steven C. H., Jialei Wang, Peilin Zhao, Zhi-Yong Liu
Research Collection School Of Computing and Information Systems
In this paper, we present a new framework for large scale online kernel learning, making kernel methods efficient and scalable for large-scale online learning applications. Unlike the regular budget online kernel learning scheme that usually uses some budget maintenance strategies to bound the number of support vectors, our framework explores a completely different approach of kernel functional approximation techniques to make the subsequent online learning task efficient and scalable. Specifically, we present two different online kernel machine learning algorithms: (i) Fourier Online Gradient Descent (FOGD) algorithm that applies the random Fourier features for approximating kernel functions; and (ii) Nyström Online …
When Peculiarity Makes A Difference: Object Characterisation In Heterogeneous Information Networks, Wei Chen, Feida Zhu, Lei Zhao, Xiaofang Zhou
When Peculiarity Makes A Difference: Object Characterisation In Heterogeneous Information Networks, Wei Chen, Feida Zhu, Lei Zhao, Xiaofang Zhou
Research Collection School Of Computing and Information Systems
A central task in heterogeneous information networks (HIN) is how to characterise an entity, which underlies a wide range of applications such as similarity search, entity profiling and linkage. Most existing work focus on using the main features common to all. While this approach makes sense in settings where commonality is of primary interest, there are many scenarios as important where uncommon and discriminative features are more useful. To address the problem, a novel model COHIN (Characterize Objects in Heterogeneous Information Networks) is proposed, where each object is characterized as a set of feature paths that contain both main and …
Opinion Question Answering By Sentiment Clip Localization, Lei Pang, Chong-Wah Ngo
Opinion Question Answering By Sentiment Clip Localization, Lei Pang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This article considers multimedia question answering beyond factoid and how-to questions. We are interested in searching videos for answering opinion-oriented questions that are controversial and hotly debated. Examples of questions include "Should Edward Snowden be pardoned?" and "Obamacare-unconstitutional or not?". These questions often invoke emotional response, either positively or negatively, hence are likely to be better answered by videos than texts, due to the vivid display of emotional signals visible through facial expression and speaking tone. Nevertheless, a potential answer of duration 60s may be embedded in a video of 10min, resulting in degraded user experience compared to reading the …
Feature Knowledge Based Fault Detection Of Induction Motors Through The Analysis Of Stator Current Data, Ting Yang, Haibo Pen, Zhaoxia Wang, Che Sau Chang
Feature Knowledge Based Fault Detection Of Induction Motors Through The Analysis Of Stator Current Data, Ting Yang, Haibo Pen, Zhaoxia Wang, Che Sau Chang
Research Collection School Of Computing and Information Systems
The fault detection of electrical or mechanical anomalies in induction motors has been a challenging problem for researchers over decades to ensure the safety and economic operations of industrial processes. To address this issue, this paper studies the stator current data obtained from inverter-fed laboratory induction motors and investigates the unique signatures of the healthy and faulty motors with the aim of developing knowledge based fault detection method for performing online detection of motor fault problems, such as broken-rotor-bar and bearing faults. Stator current data collected from induction motors were analyzed by leveraging fast Fourier transform (FFT), and the FFT …
Interactive Teachable Cognitive Agents: Smart Building Blocks For Multiagent Systems, Budhitama Subagdja, Ah-Hwee Tan
Interactive Teachable Cognitive Agents: Smart Building Blocks For Multiagent Systems, Budhitama Subagdja, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Developing a complex intelligent system by abstracting their behaviors, functionalities, and reasoning mechanisms can be tedious and time consuming. In this paper, we present a framework for developing an application or software system based on smart autonomous components that collaborate with the developer or user to realize the entire system. Inspired by teachable approaches and programming-by-demonstration methods in robotics and end-user development, we treat intelligent agents as teachable components that make up the system to be built. Each agent serves different functionalities and may have prebuilt operations to accomplish its own design objectives. However, each agent may also be equipped …
Sinabro: A Smartphone-Integrated Opportunistic Electrocardiogram Monitoring System, Sungjun Kwon, Dongseok Lee, Jeehoon Kim, Youngki Lee, Seungwoo Kang, Sangwon Seo, Kwangsuk Park
Sinabro: A Smartphone-Integrated Opportunistic Electrocardiogram Monitoring System, Sungjun Kwon, Dongseok Lee, Jeehoon Kim, Youngki Lee, Seungwoo Kang, Sangwon Seo, Kwangsuk Park
Research Collection School Of Computing and Information Systems
In our preliminary study, we proposed a smartphone-integrated, unobtrusive electrocardiogram (ECG) monitoring system, Sinabro, which monitors a user's ECG opportunistically during daily smartphone use without explicit user intervention. The proposed system also monitors ECG-derived features, such as heart rate (HR) and heart rate variability (HRV), to support the pervasive healthcare apps for smartphones based on the user's high-level contexts, such as stress and affective state levels. In this study, we have extended the Sinabro system by: (1) upgrading the sensor device; (2) improving the feature extraction process; and (3) evaluating extensions of the system. We evaluated these extensions with a …
History Driven Program Repair, Xuan-Bach D. Le, David Lo, Claire Le Goues
History Driven Program Repair, Xuan-Bach D. Le, David Lo, Claire Le Goues
Research Collection School Of Computing and Information Systems
Effective automated program repair techniques have great potential to reduce the costs of debugging and maintenance. Previously proposed automated program repair (APR) techniques often follow a generate-and-validate and test- case-driven procedure: They first randomly generate a large pool of fix candidates and then exhaustively validate the quality of the candidates by testing them against existing or provided test suites. Unfortunately, many real-world bugs cannot be repaired by existing techniques even after more than 12 hours of computation in a multi-core cloud environment. More work is needed to advance the capabilities of modern APR techniques. We propose a new technique that …
Diversity Maximization Speedup For Localizing Faults In Single-Fault And Multi-Fault Programs, Xin Xia, Liang Gong, Tien-Duy B. Le, David Lo, Lingxiao Jiang, Hongyu Zhang
Diversity Maximization Speedup For Localizing Faults In Single-Fault And Multi-Fault Programs, Xin Xia, Liang Gong, Tien-Duy B. Le, David Lo, Lingxiao Jiang, Hongyu Zhang
Research Collection School Of Computing and Information Systems
Fault localization is useful for reducing debugging effort. Such techniques require test cases with oracles, which can determine whether a program behaves correctly for every test input. Although most fault localization techniques can localize faults relatively accurately even with a small number of test cases, choosing the right test cases and creating oracles for them are not easy. Test oracle creation is expensive because it can take much manual labeling effort (i.e., effort needed to decide whether the test cases pass or fail). Given a number of test cases to be executed, it is challenging to minimize the number of …
Cca-Secure Keyed-Fully Homomorphic Encryption, Junzuo Lai, Deng, Robert H., Changshe Ma, Kouichi Sakurai, Jian Weng
Cca-Secure Keyed-Fully Homomorphic Encryption, Junzuo Lai, Deng, Robert H., Changshe Ma, Kouichi Sakurai, Jian Weng
Research Collection School Of Computing and Information Systems
To simultaneously achieve CCA security and homomorphic property for encryption, Emura et al. introduced a new cryptographic primitive named keyed-homomorphic encryption, in which homomorphic ciphertext manipulations can only be performed by someone holding a devoted evaluation key which, by itself, does not enable decryption. A keyed-homomorphic encryption scheme should provide CCA2 security when the evaluation key is unavailable to the adversary and remain CCA1-secure when the evaluation key is exposed. While existing keyed-homomorphic encryption schemes only allow simple computations on encrypted data, our goal is to construct CCA-secure keyed-fully homomorphic encryption (keyed-FHE) capable of evaluating any functions on encrypted data …
A Large Scale Study Of Multiple Programming Languages And Code Quality, Pavneet Singh Kochhar, Withthige Dinusha Ruchira Wijedasa, David Lo
A Large Scale Study Of Multiple Programming Languages And Code Quality, Pavneet Singh Kochhar, Withthige Dinusha Ruchira Wijedasa, David Lo
Research Collection School Of Computing and Information Systems
Nowadays, most software use multiple programming languages to implement certain functionalities based on the strengths and weaknesses of different languages. Researchers in the past have studied the impact of independent programming languages on software quality, however, there has been little or no research on the impact of multiple languages on the quality of software. Does the use of multiple languages cause more bugs? Are certain languages when used with other languages make software more bug prone? What are the relationships between multi-language usage and various bug categories? In this study, we perform a large scale empirical investigation to shed light …
A More Accurate Model For Finding Tutorial Segments Explaining Apis, He Jiang, Jingxuan Zhang, Xiaochen Li, Zhilei Ren, David Lo
A More Accurate Model For Finding Tutorial Segments Explaining Apis, He Jiang, Jingxuan Zhang, Xiaochen Li, Zhilei Ren, David Lo
Research Collection School Of Computing and Information Systems
Developers prefer to utilize third-party libraries when they implement some functionalities and Application Programming Interfaces (APIs) are frequently used by them. Facing an unfamiliar API, developers tend to consult tutorials as learning resources. Unfortunately, the segments explaining a specific API scatter across tutorials. Hence, it remains a challenging issue to find the relevant segments. In this study, we propose a more accurate model to find the exact tutorial fragments explaining APIs. This new model consists of a text classifier with domain specific features. More specifically, we discover two important indicators to complement traditional text based features, namely co-occurrence APIs and …
Strongly Leakage-Resilient Authenticated Key Exchange, Rongmao Chen, Yi Mu, Guomin Yang, Willy Susilo, Fuchun Guo
Strongly Leakage-Resilient Authenticated Key Exchange, Rongmao Chen, Yi Mu, Guomin Yang, Willy Susilo, Fuchun Guo
Research Collection School Of Computing and Information Systems
Authenticated Key Exchange (AKE) protocols have been widely deployed in many real-world applications for securing communication channels. In this paper, we make the following contributions. First, we revisit the security modelling of leakage-resilient AKE protocols, and show that the existing models either impose some unnatural restrictions or do not sufficiently capture leakage attacks in reality. We then introduce a new strong yet meaningful security model, named challenge-dependent leakage-resilient eCK (CLR- eCKCLR- eCK) model, to capture challenge-dependent leakage attacks on both long-term secret key and ephemeral secret key (i.e., randomness). Second, we propose a general framework for constructing one-round CLR- eCKCLR- …
A Business Zone Recommender System Based On Facebook And Urban Planning Data, Jovian Lin, Richard Jayadi Oentaryo, Ee Peng Lim, Casey Vu, Adrian Wei Liang Vu, Philips Kokoh And Prasetyo
A Business Zone Recommender System Based On Facebook And Urban Planning Data, Jovian Lin, Richard Jayadi Oentaryo, Ee Peng Lim, Casey Vu, Adrian Wei Liang Vu, Philips Kokoh And Prasetyo
Research Collection School Of Computing and Information Systems
We present ZoneRec—a zone recommendation system for physical businesses in an urban city,which uses both public business data from Facebook and urban planning data. The systemconsists of machine learning algorithms that take in a business’ metadata and outputs a list ofrecommended zones to establish the business in. We evaluate our system using data of foodbusinesses in Singapore and assess the contribution of different feature groups to therecommendation quality.
Iris: Tapping Wearable Sensing To Capture In-Store Retail Insights On Shoppers, Meera Radhakrishnan, Sharanya Eswaran, Archan Misra, Deepthi Chander, Koustuv Dasgupta
Iris: Tapping Wearable Sensing To Capture In-Store Retail Insights On Shoppers, Meera Radhakrishnan, Sharanya Eswaran, Archan Misra, Deepthi Chander, Koustuv Dasgupta
Research Collection School Of Computing and Information Systems
We investigate the possibility of using a combination of a smartphone and a smartwatch, carried by a shopper, to get insights into the shopper’s behavior inside a retail store. The proposed IRIS framework uses standard locomotive and gestural micro-activities as building blocks to define novel composite features that help classify different facets of a shopper’s interaction/experience with individual items, as well as attributes of the overall shopping episode or the store. Besides defining such novel features, IRIS builds a novel segmentation algorithm, which partitions the duration of an entire shopping episode into atomic item-level interactions, by using a combination of …
Scrum-X: An Interactive And Experiential Learning Platform For Teaching Scrum, Wee Leong Lee
Scrum-X: An Interactive And Experiential Learning Platform For Teaching Scrum, Wee Leong Lee
Research Collection School Of Computing and Information Systems
Motivating and engaging thecurrent generation of technology-savvy students and improving the quality oflearning is becoming more challenging with traditional instructional methods.Educational games and simulations are gaining more ground, both in formal andinformal learning environments. With experiential learning, learners canenhance their management skills and ability to make decisions by analyzingdifferent scenarios and paths that the project could have taken if specificdecisions were made during the project. This paper presents Scrum-X, acomputer-based simulation game to teach Scrum, an agile project managementmethodology, to graduates and professionals with IT background. In the game,players plan, execute and manage a software development project using Scrummethodology. Players …
Rack: Automatic Api Recommendation Using Crowdsourced Knowledge, Mohammad M. Rahman, Chanchal K. Roy, David Lo
Rack: Automatic Api Recommendation Using Crowdsourced Knowledge, Mohammad M. Rahman, Chanchal K. Roy, David Lo
Research Collection School Of Computing and Information Systems
Traditional code search engines often do not perform well with natural language queries since they mostly apply keyword matching. These engines thus need carefully designed queries containing information about programming APIs for code search. Unfortunately, existing studies suggest that preparing an effective code search query is both challenging and time consuming for the developers. In this paper, we propose a novel API recommendation technique -- RACK that recommends a list of relevant APIs for a natural language query for code search by exploiting keyword-API associations from the crowdsourced knowledge of Stack Overflow. We first motivate our technique using an exploratory …
Ranking Of High-Value Social Audiences On Twitter, Siaw Ling Lo, Raymond Chiong, David Cornforth
Ranking Of High-Value Social Audiences On Twitter, Siaw Ling Lo, Raymond Chiong, David Cornforth
Research Collection School Of Computing and Information Systems
Even though social media offers plenty of business opportunities, for a company to identify the right audience from the massive amount of social media data is highly challenging given finite resources and marketing budgets. In this paper, we present a ranking mechanism that is capable of identifying the top-k social audience members on Twitter based on an index. Data from three different Twitter business account owners were used in our experiments to validate this ranking mechanism. The results show that the index developed using a combination of semi-supervised and supervised learning methods is indeed generic enough to retrieve relevant audience …
Mobile App Tagging, Ning Chen, Steven C. H. Hoi, Shaohua Li, Xiaokui Xiao
Mobile App Tagging, Ning Chen, Steven C. H. Hoi, Shaohua Li, Xiaokui Xiao
Research Collection School Of Computing and Information Systems
Mobile app tagging aims to assign a list of keywords indicating core functionalities, main contents, key features or concepts of a mobile app. Mobile app tags can be potentially useful for app ecosystem stakeholders or other parties to improve app search, browsing, categorization, and advertising, etc. However, most mainstream app markets, e.g., Google Play, Apple App Store, etc., currently do not explicitly support such tags for apps. To address this problem, we propose a novel auto mobile app tagging framework for annotating a given mobile app automatically, which is based on a search-based annotation paradigm powered by machine learning techniques. …
Multiagent-Based Route Guidance For Increasing The Chance Of Arrival On Time, Zhiguang Cao, Hongliang Guo, Jie Zhang, Ulrich Fastenrath
Multiagent-Based Route Guidance For Increasing The Chance Of Arrival On Time, Zhiguang Cao, Hongliang Guo, Jie Zhang, Ulrich Fastenrath
Research Collection School Of Computing and Information Systems
Transportation and mobility are central to sustainable urban development, where multiagent-based route guidance is widely applied. Traditional multiagent-based route guidance always seeks LET (least expected travel time) paths. However, drivers usually have specific expectations, i.e., tight or loose deadlines, which may not be all met by LET paths. We thus adopt and extend the probability tail model that aims to maximize the probability of reaching destinations before deadlines. Specifically, we propose a decentralized multiagent approach, where infrastructure agents locally collect intentions of concerned vehicle agents and formulate route guidance as a route assignment problem, to guarantee their arrival on time. …