Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Databases and Information Systems (3446)
- Software Engineering (2149)
- Artificial Intelligence and Robotics (1675)
- Information Security (1059)
- Numerical Analysis and Scientific Computing (1024)
-
- Graphics and Human Computer Interfaces (924)
- Engineering (858)
- Social and Behavioral Sciences (661)
- Business (627)
- Theory and Algorithms (493)
- Computer Engineering (431)
- Operations Research, Systems Engineering and Industrial Engineering (400)
- Programming Languages and Compilers (379)
- OS and Networks (323)
- Communication (297)
- Social Media (240)
- Public Affairs, Public Policy and Public Administration (207)
- Transportation (185)
- Medicine and Health Sciences (178)
- Education (164)
- Management Information Systems (164)
- Data Storage Systems (160)
- E-Commerce (146)
- Health Information Technology (107)
- International and Area Studies (107)
- Asian Studies (106)
- Technology and Innovation (101)
- Digital Communications and Networking (96)
- Keyword
-
- Deep learning (123)
- Machine learning (121)
- Social media (74)
- Artificial intelligence (70)
- Reinforcement learning (69)
-
- Data mining (64)
- Privacy (61)
- Cloud computing (58)
- Deep Learning (56)
- Empirical study (54)
- Optimization (53)
- Security (53)
- Visualization (51)
- Software engineering (49)
- Training (49)
- Neural networks (48)
- Online learning (48)
- Task analysis (48)
- Anomaly detection (47)
- Singapore (47)
- Twitter (46)
- Feature extraction (45)
- Blockchain (44)
- Collaboration (44)
- Large Language Models (44)
- Semantics (43)
- Access control (41)
- Algorithms (40)
- Android (39)
- Machine Learning (38)
- Publication Year
- File Type
Articles 4291 - 4320 of 8495
Full-Text Articles in Computer Sciences
Combination Forecasting Reversion Strategy For Online Portfolio Selection, Dingjiang Huang, Shunchang Yu, Bin Li, Steven C. H. Hoi, Shuigeng G. Zhou
Combination Forecasting Reversion Strategy For Online Portfolio Selection, Dingjiang Huang, Shunchang Yu, Bin Li, Steven C. H. Hoi, Shuigeng G. Zhou
Research Collection School Of Computing and Information Systems
Machine learning and artificial intelligence techniques have been applied to construct online portfolio selection strategies recently. A popular and state-of-the-art family of strategies is to explore the reversion phenomenon through online learning algorithms and statistical prediction models. Despite gaining promising results on some benchmark datasets, these strategies often adopt a single model based on a selection criterion (e.g., breakdown point) for predicting future price. However, such model selection is often unstable and may cause unnecessarily high variability in the final estimation, leading to poor prediction performance in real datasets and thus non-optimal portfolios. To overcome the drawbacks, in this article, …
Real World, Large Scale Iot Systems For Community Eldercare: Experiences And Lessons Learned, Alvin Cerdena Valera, Wei Qi Lee, Hwee-Pink Tan, Hwee Xian Tan, Huiguang Liang
Real World, Large Scale Iot Systems For Community Eldercare: Experiences And Lessons Learned, Alvin Cerdena Valera, Wei Qi Lee, Hwee-Pink Tan, Hwee Xian Tan, Huiguang Liang
Research Collection School Of Computing and Information Systems
The paradigm of aging-in-place - where the elderly live and age in their own homes, independently and safely, with care provided by the community - is compelling, especially in societies that face both shortages in institutionalized eldercare resources, and rapidly-aging populations. When the number of elderly who live alone rises rapidly, support and care from their communities become increasingly critical. Internet-of-Things(IoT) technologies, particularly in-home monitoring solutions, are becoming mature. They can become the fundamental enabler for smart community eldercare. In this chapter, we share our real-world experiencesgleaned from an ongoing large-scale project on IoT-enabled community eldercare. We identify technology-centric challenges …
Vocal Programming For People With Upper-Body Motor Impairments, Lucas Rosenblatt, Patrick Carrington, Kotaro Hara, Jeffrey P. Bigham
Vocal Programming For People With Upper-Body Motor Impairments, Lucas Rosenblatt, Patrick Carrington, Kotaro Hara, Jeffrey P. Bigham
Research Collection School Of Computing and Information Systems
Programming heavily relies on entering text using traditional QWERTY keyboards, which poses challenges for people with limited upper-body movement. Developing tools using a publicly available speech recognition API could provide a basis for keyboard free programming. In this paper, we describe our efforts in design, development, and evaluation of a voice-based IDE to support people with limited dexterity.
Feature Engineering For Machine Learning And Data Analytics, Xin Xia, David Lo
Feature Engineering For Machine Learning And Data Analytics, Xin Xia, David Lo
Research Collection School Of Computing and Information Systems
This chapter provides an introduction on feature generation and engineering for software analytics. Specifically, we show how domain-specifc features can be designed and used to automate three software engineering tasks: (1) detecting defective software modules (defect prediction), (2) identifying crashing mobile app release (crash release prediction), and (3) predicting who will leave a software team (developer turnover prediction). For each of the three tasks, different sets of features are extracted from a diverse set of software artifacts, and used to build predictive models.
A Visual Interaction Cue Framework From Video Game Environments For Augmented Reality, Kody R. Dillman, Terrance Tin Hoi Mok, Anthony Tang, Lora Oehlberg, Alex Mitchell
A Visual Interaction Cue Framework From Video Game Environments For Augmented Reality, Kody R. Dillman, Terrance Tin Hoi Mok, Anthony Tang, Lora Oehlberg, Alex Mitchell
Research Collection School Of Computing and Information Systems
Based on an analysis of 49 popular contemporary video games, we develop a descriptive framework of visual interaction cues in video games. These cues are used to inform players what can be interacted with, where to look, and where to go within the game world. These cues vary along three dimensions: the purpose of the cue, the visual design of the cue, and the circumstances under which the cue is shown. We demonstrate that this framework can also be used to describe interaction cues for augmented reality applications. Beyond this, we show how the framework can be used to generatively …
Geocaching With A Beam: Shared Outdoor Activities Through A Telepresence Robot With 360 Degree Viewing, Yasamin Heshmat, Brennan Jones, Xiaoxuan Xiong, Carman Neustaedter, Anthony Tang, Bernhard E. Riecke, Lillian Yang
Geocaching With A Beam: Shared Outdoor Activities Through A Telepresence Robot With 360 Degree Viewing, Yasamin Heshmat, Brennan Jones, Xiaoxuan Xiong, Carman Neustaedter, Anthony Tang, Bernhard E. Riecke, Lillian Yang
Research Collection School Of Computing and Information Systems
People often enjoy sharing outdoor activities together such as walking and hiking. However, when family and friends are separated by distance it can be difficult if not impossible to share such activities. We explore this design space by investigating the benefits and challenges of using a telepresence robot to support outdoor leisure activities. In our study, participants participated in the outdoor activity of geocaching where one person geocached with the help of a remote partner via a telepresence robot. We compared a wide field of view (WFOV) camera to a 360° camera. Results show the benefits of having a physical …
Persona Perception Scale: Developing And Validating An Instrument For Human-Like Representations Of Data, Salminen Joni, Haewoon Kwak, João Santos, Soon-Gyo Jung, Jisun An, Bernard J. Jansen
Persona Perception Scale: Developing And Validating An Instrument For Human-Like Representations Of Data, Salminen Joni, Haewoon Kwak, João Santos, Soon-Gyo Jung, Jisun An, Bernard J. Jansen
Research Collection School Of Computing and Information Systems
Personas are widely used in software development, system design, and HCI studies. Yet, their evaluation is difficult, and there are no recognized and validated measurement scales to date. To improve this condition, this research develops a persona perception scale based on reviewing relevant literature. We validate the scale through a pilot study with 19 participants, each evaluating three personas (57 evaluations in total). This is the first reported effort to systematically develop and validate an instrument for persona perception measurement. We find the constructs and items of the scale perform well, with factor loadings ranging between 0.60 and 0.95. Reliability, …
Deeprefiner: Multi-Layer Android Malware Detection System Applying Deep Neural Networks, Xu Ke, Yingjiu Li, Robert H. Deng, Kai Chen
Deeprefiner: Multi-Layer Android Malware Detection System Applying Deep Neural Networks, Xu Ke, Yingjiu Li, Robert H. Deng, Kai Chen
Research Collection School Of Computing and Information Systems
As malicious behaviors vary significantly across mobile malware, it is challenging to detect malware both efficiently and effectively. Also due to the continuous evolution of malicious behaviors, it is difficult to extract features by laborious human feature engineering and keep up with the speed of malware evolution. To solve these challenges, we propose DeepRefiner to identify malware both efficiently and effectively. The novel technique enabling effectiveness is the semantic-based deep learning. We use Long Short Term Memory on the semantic structure of Android bytecode, avoiding missing the details of method-level bytecode semantics. To achieve efficiency, we apply Multilayer Perceptron on …
Entagrec(++): An Enhanced Tag Recommendation System For Software Information Sites, Shaowei Wang, David Lo, Bogdan Vasilescu, Alexander Serebrenik
Entagrec(++): An Enhanced Tag Recommendation System For Software Information Sites, Shaowei Wang, David Lo, Bogdan Vasilescu, Alexander Serebrenik
Research Collection School Of Computing and Information Systems
Software engineers share experiences with modern technologies by means of software information sites, such as Stack Overflow. These sites allow developers to label posted content, referred to as software objects, with short descriptions, known as tags. However, tags assigned to objects tend to be noisy and some objects are not well tagged. To improve the quality of tags in software information sites, we propose EnTagRec, an automatic tag recommender based on historical tag assignments to software objects and we evaluate its performance on four software information sites, Stack Overflow, Ask Ubuntu, Ask Different, and Free code. We observe that that …
The Impact Of Rapid Release Cycles On The Integration Delay Of Fixed Issues, Daniel Alencar Da Costa, Shane Mcintosh, Christoph Treude, Uirá Kulesza, Ahmed E. Hassan
The Impact Of Rapid Release Cycles On The Integration Delay Of Fixed Issues, Daniel Alencar Da Costa, Shane Mcintosh, Christoph Treude, Uirá Kulesza, Ahmed E. Hassan
Research Collection School Of Computing and Information Systems
The release frequency of software projects has increased in recent years. Adopters of so-called rapid releases—short release cycles, often on the order of weeks, days, or even hours—claim that they can deliver fixed issues (i.e., implemented bug fixes and new features) to users more quickly. However, there is little empirical evidence to support these claims. In fact, our prior work shows that code integration phases may introduce delays for rapidly releasing projects—98% of the fixed issues in the rapidly releasing Firefox project had their integration delayed by at least one release. To better understand the impact that rapid release cycles …
Demo Abstract: Simultaneous Energy Harvesting And Sensing Using Piezoelectric Energy Harvester, Dong Ma, Guohao Lan, Weitao Xu, Mahbub Hassan, Wen Hu
Demo Abstract: Simultaneous Energy Harvesting And Sensing Using Piezoelectric Energy Harvester, Dong Ma, Guohao Lan, Weitao Xu, Mahbub Hassan, Wen Hu
Research Collection School Of Computing and Information Systems
With the capability to harvest energy from low frequency motions or vibrations, piezoelectric energy harvesting has become a promising solution to achieve battery-less wearable system. Recently, many works have convincingly demonstrated that PEH can also act as a self-powered sensor for detecting a wide range of machine and human contexts, which suggests that energy harvesting and sensing can be performed concurrently. However, realization of simultaneous energy harvesting and sensing (SEHS) is challenging as the energy harvesting process distorts the sensing signal. In this demo, we propose a novel SEHS architecture prototyped in the form factor of an insole, which combines …
Sehs: Simultaneous Energy Harvesting And Sensing Using Piezoelectric Energy Harvester, Dong Ma, Guohan Lan, Weitao Xu, Mahbub Hassan, Wen Hu
Sehs: Simultaneous Energy Harvesting And Sensing Using Piezoelectric Energy Harvester, Dong Ma, Guohan Lan, Weitao Xu, Mahbub Hassan, Wen Hu
Research Collection School Of Computing and Information Systems
Piezoelectric energy harvesting (PEH), which converts ambient motion, stress, and vibrations into usable electricity, may help combat battery issues in a growing number of industrial and wearable Internet of things (IoTs). Recently, many works have convincingly demonstrated that PEH can also act as a self-powered sensor for detecting a wide range of machine and human contexts. These developments suggest that the same PEH hardware could be potentially used for simultaneous energy harvesting and sensing (SEHS), offering a new design space for low cost and low power IoT devices. Unfortunately, realization of SEHS is challenging as the energy harvesting process distorts …
Findings Of A User Study Of Automatically Generated Personas, Joni Salminen, Haewoon Kwak, Jisun An, Soon-Gyo Jung, Bernard J. Jansen
Findings Of A User Study Of Automatically Generated Personas, Joni Salminen, Haewoon Kwak, Jisun An, Soon-Gyo Jung, Bernard J. Jansen
Research Collection School Of Computing and Information Systems
We report findings and implications from a semi-naturalistic user study of a system for Automatic Persona Generation (APG) using large-scale audience data of an organization's social media channels conducted at the workplace of a major international corporation. Thirteen participants from a range of positions within the company engaged with the system in a use case scenario. We employed a variety of data collection methods, including mouse tracking and survey data, analyzing the data with a mixed method approach. Results show that having an interactive system may aid in keeping personas at the forefront while making customer-centric decisions and indicate that …
Social Network Monitoring For Bursty Cascade Detection, Wei Xie, Feida Zhu, Jing Xiao, Jianzong Wang
Social Network Monitoring For Bursty Cascade Detection, Wei Xie, Feida Zhu, Jing Xiao, Jianzong Wang
Research Collection School Of Computing and Information Systems
Social network services have become important and efficient platforms for users to share all kinds of information. The capability to monitor user-generated information and detect bursts from information diffusions in these social networks brings value to a wide range of real-life applications, such as viral marketing. However, in reality, as a third party, there is always a cost for gathering information from each user or so-called social network sensor. The question then arises how to select a budgeted set of social network sensors to form the data stream for burst detection without compromising the detection performance. In this article, we …
Detect Rumor And Stance Jointly By Neural Multi-Task Learning, Jing Ma, Wei Gao, Kam-Fai Wong
Detect Rumor And Stance Jointly By Neural Multi-Task Learning, Jing Ma, Wei Gao, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
In recent years, an unhealthy phenomenon characterized as the massive spread of fake news or unverified information (i.e., rumors) has become increasingly a daunting issue in human society. The rumors commonly originate from social media outlets, primarily microblogging platforms, being viral afterwards by the wild, willful propagation via a large number of participants. It is observed that rumorous posts often trigger versatile, mostly controversial stances among participating users. Thus, determining the stances on the posts in question can be pertinent to the successful detection of rumors, and vice versa. Existing studies, however, mainly regard rumor detection and stance classification as …
Frame Inference For Inductive Entailment Proofs In Separation Logic, Quang Loc Le, Jun Sun, Shengchao Qin
Frame Inference For Inductive Entailment Proofs In Separation Logic, Quang Loc Le, Jun Sun, Shengchao Qin
Research Collection School Of Computing and Information Systems
Given separation logic formulae A and C, frame inference is the problem of checking whether A entails C and simultaneously inferring residual heaps. Existing approaches on frame inference do not support inductive proofs with general inductive predicates. In this work, we present an automatic frame inference approach for an expressive fragment of separation logic. We further show how to strengthen the inferred frame through predicate normalization and arithmetic inference. We have integrated our approach into an existing verification system. The experimental results show that our approach helps to establish a number of non-trivial inductive proofs which are beyond the capability …
Distributed Multi-Task Classification: A Decentralized Online Learning Approach, Chi Zhang, Peilin Zhao, Shuji Hao, Yeng Chai Soh, Bu Sung Lee, Chunyan Miao, Steven C. H. Hoi
Distributed Multi-Task Classification: A Decentralized Online Learning Approach, Chi Zhang, Peilin Zhao, Shuji Hao, Yeng Chai Soh, Bu Sung Lee, Chunyan Miao, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Although dispersing one single task to distributed learning nodes has been intensively studied by the previous research, multi-task learning on distributed networks is still an area that has not been fully exploited, especially under decentralized settings. The challenge lies in the fact that different tasks may have different optimal learning weights while communication through the distributed network forces all tasks to converge to an unique classifier. In this paper, we present a novel algorithm to overcome this challenge and enable learning multiple tasks simultaneously on a decentralized distributed network. Specifically, the learning framework can be separated into two phases: (i) …
Does Journaling Encourage Healthier Choices? Analyzing Healthy Eating Behaviors Of Food Journalers, Palakorn Achananuparp, Ee Peng Lim, Vibhanshu Abhishek
Does Journaling Encourage Healthier Choices? Analyzing Healthy Eating Behaviors Of Food Journalers, Palakorn Achananuparp, Ee Peng Lim, Vibhanshu Abhishek
Research Collection School Of Computing and Information Systems
Past research has shown the benefits of food journaling in promoting mindful eating and healthier food choices. However, the links between journaling and healthy eating have not been thoroughly examined. Beyond caloric restriction, do journalers consistently and sufficiently consume healthful diets? How different are their eating habits compared to those of average consumers who tend to be less conscious about health? In this study, we analyze the healthy eating behaviors of active food journalers using data from MyFitnessPal. Surprisingly, our findings show that food journalers do not eat as healthily as they should despite their proclivity to health eating and …
Exploiting User And Venue Characteristics For Fine-Grained Tweet Geolocation, Wen Haw Chong, Ee Peng Lim
Exploiting User And Venue Characteristics For Fine-Grained Tweet Geolocation, Wen Haw Chong, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Which venue is a tweet posted from? We call this a fine-grained geolocation problem. Given an observed tweet, the task is to infer its discrete posting venue, e.g., a specific restaurant. This recovers the venue context and differs from prior work, which geolocats tweets to location coordinates or cities/neighborhoods. First, we conduct empirical analysis to uncover venue and user characteristics for improving geolocation. For venues, we observe spatial homophily, in which venues near each other have more similar tweet content (i.e., text representations) compared to venues further apart. For users, we observe that they are spatially focused and more likely …
Can Multimodal Sensing Detect And Localize Transient Events?, Kasthuri Jayarajah, Subbaraju Vigneshwaran, Noel Athaide, Lakmal Meeghapola, Andrew Tan, Archan Misra
Can Multimodal Sensing Detect And Localize Transient Events?, Kasthuri Jayarajah, Subbaraju Vigneshwaran, Noel Athaide, Lakmal Meeghapola, Andrew Tan, Archan Misra
Research Collection School Of Computing and Information Systems
With the increased focus on making cities "smarter", we see an upsurge in investment in sensing technologies embedded in the urban infrastructure. The deployment of GPS sensors aboard taxis and buses, smartcards replacing paper tickets, and other similar initiatives have led to an abundance of data on human mobility, generated at scale and available real-time. Further still, users of social media platforms such as Twitter and LBSNs continue to voluntarily share multimedia content revealing in-situ information on their respective localities. The availability of such longitudinal multimodal data not only allows for both the characterization of the dynamics of the city, …
Scalable Hypergraph-Based Image Retrieval And Tagging System, Lu Chen, Yunjun Gao, Yuanliang Zhang, Sibo Wang, Baihua Zheng
Scalable Hypergraph-Based Image Retrieval And Tagging System, Lu Chen, Yunjun Gao, Yuanliang Zhang, Sibo Wang, Baihua Zheng
Research Collection School Of Computing and Information Systems
Massive amounts of images textually annotated by different users are provided by social image websites, e.g., Flickr. Social images are always associated with various information, such as visual features, tags, and users. In this paper, we utilize hypergraph instead of ordinary graph to model social images, since relations among various information are more sophisticated than pairwise. Based on the hypergraph, we propose HIRT, a scalable image retrieval and tagging system, which uses Personalized PageRank to measure vertex similarity, and employs top-k search to support image retrieval and tagging. To achieve good scalability and efficiency, we develop parallel and approximate top-k …
Combined Classifier For Cross-Project Defect Prediction: An Extended Empirical Study, Yun Zhang, David Lo, Xin Xia, Jianling Sun
Combined Classifier For Cross-Project Defect Prediction: An Extended Empirical Study, Yun Zhang, David Lo, Xin Xia, Jianling Sun
Research Collection School Of Computing and Information Systems
To facilitate developers in effective allocation of their testing and debugging efforts, many software defect prediction techniques have been proposed in the literature. These techniques can be used to predict classes that are more likely to be buggy based on the past history of classes, methods, or certain other code elements. These techniques are effective provided that a sufficient amount of data is available to train a prediction model. However, sufficient training data are rarely available for new software projects. To resolve this problem, cross-project defect prediction, which transfers a prediction model trained using data from one project to another, …
Location-Aware Influence Maximization Over Dynamic Social Streams, Yanhao Wang, Yuchen Li, Ju Fan, Kianlee Tan
Location-Aware Influence Maximization Over Dynamic Social Streams, Yanhao Wang, Yuchen Li, Ju Fan, Kianlee Tan
Research Collection School Of Computing and Information Systems
Influence maximization (IM), which selects a set of k seed users (a.k.a., a seed set) to maximize the influence spread over a social network, is a fundamental problem in a wide range of applications. However, most existing IM algorithms are static and location-unaware. They fail to provide high-quality seed sets efficiently when the social network evolves rapidly and IM queries are location-aware. In this article, we first define two IM queries, namely Stream Influence Maximization (SIM) and Location-aware SIM (LSIM), to track influential users over social streams. Technically, SIM adopts the sliding window model and maintains a seed set with …
Continuous Top-K Monitoring On Document Streams (Extended Abstract), Leong Hou U, Junjie Zhang, Kyriakos Mouratidis, Ye Li
Continuous Top-K Monitoring On Document Streams (Extended Abstract), Leong Hou U, Junjie Zhang, Kyriakos Mouratidis, Ye Li
Research Collection School Of Computing and Information Systems
The efficient processing of document streams plays an important role in many information filtering systems. Emerging applications, such as news update filtering and social network notifications, demand presenting end-users with the most relevant content to their preferences. In this work, user preferences are indicated by a set of keywords. A central server monitors the document stream and continuously reports to each user the top-k documents that are most relevant to her keywords. The objective is to support large numbers of users and high stream rates, while refreshing the topk results almost instantaneously. Our solution abandons the traditional frequency-ordered indexing approach, …
A Data-Driven Analysis Of Workers' Earnings On Amazon Mechanical Turk, Kotaro Hara, Abigail Adams, Kristy Milland, Saiph Savage, Chris Callison-Burch, Jeffrey P. Bigham
A Data-Driven Analysis Of Workers' Earnings On Amazon Mechanical Turk, Kotaro Hara, Abigail Adams, Kristy Milland, Saiph Savage, Chris Callison-Burch, Jeffrey P. Bigham
Research Collection School Of Computing and Information Systems
A growing number of people are working as part of on-line crowd work. Crowd work is often thought to be low wage work. However, we know little about the wage distribution in practice and what causes low/high earnings in this setting. We recorded 2,676 workers performing 3.8 million tasks on Amazon Mechanical Turk. Our task-level analysis revealed that workers earned a median hourly wage of only ~$2/h, and only 4% earned more than $7.25/h. While the average requester pays more than $11/h, lower-paying requesters post much more work. Our wage calculations are influenced by how unpaid work is accounted for, …
Latency-Oriented Task Completion Via Spatial Crowdsourcing, Yuxiang Zeng, Yongxin Tong, Lei Chen, Zimu Zhou
Latency-Oriented Task Completion Via Spatial Crowdsourcing, Yuxiang Zeng, Yongxin Tong, Lei Chen, Zimu Zhou
Research Collection School Of Computing and Information Systems
Spatial crowdsourcing brings in a new approach for social media and location-based services (LBS) to collect locationspecific information via mobile users. For example, when a user checks in at a shop on Facebook, he will immediately receive and is asked to complete a set of tasks such as “what is the opening hour of the shop”. It is non-trivial to complete a set of tasks timely and accurately via spatial crowdsourcing. Since workers in spatial crowdsourcing are often transient and limited in number, these social media platforms need to properly allocate workers within the set of tasks such that all …
'Is More Better?': Impact Of Multiple Photos On Perception Of Persona Profiles, Joni Salminen, Lene Nielsen, Soon-Gyo Jung, Jisun An, Haewoon Kwak, Bernard J. Jansen
'Is More Better?': Impact Of Multiple Photos On Perception Of Persona Profiles, Joni Salminen, Lene Nielsen, Soon-Gyo Jung, Jisun An, Haewoon Kwak, Bernard J. Jansen
Research Collection School Of Computing and Information Systems
In this research, we investigate if and how more photos than a single headshot can heighten the level of information provided by persona profiles. We conduct eye-tracking experiments and qualitative interviews with variations in the photos: a single headshot, a headshot and images of the persona in different contexts, and a headshot with pictures of different people representing key persona attributes. The results show that more contextual photos significantly improve the information end users derive from a persona profile; however, showing images of different people creates confusion and lowers the informativeness. Moreover, we discover that choice of pictures results in …
Crowdservice: Optimizing Mobile Crowdsourcing And Service Composition, Xin Peng, Jingxiao Gu, Tian Huat Tan, Jun Sun, Yijun Yu, Bashar Nuseibeh, Wenyun Zhao Zhao
Crowdservice: Optimizing Mobile Crowdsourcing And Service Composition, Xin Peng, Jingxiao Gu, Tian Huat Tan, Jun Sun, Yijun Yu, Bashar Nuseibeh, Wenyun Zhao Zhao
Research Collection School Of Computing and Information Systems
Some user needs can only be met by leveraging the capabilities of others to undertake particular tasks that require intelligence and labor. Crowdsourcing such capabilities is one way to achieve this. But providing a service that leverages crowd intelligence and labor is a challenge, since various factors need to be considered to enable reliable service provisioning. For example, the selection of an optimal set of workers from those who bid to perform a task needs to be made based on their reliability, expected reward, and distance to the target locations. Moreover, for an application involving multiple services, the overall cost …
Attributed Social Network Embedding, Lizi Liao, Xiangnan He, Hanwang Zhang, Tat-Seng Chua
Attributed Social Network Embedding, Lizi Liao, Xiangnan He, Hanwang Zhang, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Embedding network data into a low-dimensional vector space has shown promising performance for many real-world applications, such as node classification and entity retrieval. However, most existing methods focused only on leveraging network structure. For social networks, besides the network structure, there also exists rich information about social actors, such as user profiles of friendship networks and textual content of citation networks. These rich attribute information of social actors reveal the homophily effect, exerting huge impacts on the formation of social networks. In this paper, we explore the rich evidence source of attributes in social networks to improve network embedding. We …
Fixation And Confusion: Investigating Eye-Tracking Participants' Exposure To Information In Personas, Joni Salminen, Bernard J. Jansen, Jisun An, Soon-Gyo Jung, Lene Nielsen, Haewoon Kwak
Fixation And Confusion: Investigating Eye-Tracking Participants' Exposure To Information In Personas, Joni Salminen, Bernard J. Jansen, Jisun An, Soon-Gyo Jung, Lene Nielsen, Haewoon Kwak
Research Collection School Of Computing and Information Systems
To more effectively convey relevant information to end users of persona profiles, we conducted a user study consisting of 29 participants engaging with three persona layout treatments. We were interested in confusion engendered by the treatments on the participants, and conducted a within-subjects study in the actual work environment, using eye-tracking and talk-aloud data collection. We coded the verbal data into classes of informativeness and confusion and correlated it with fixations and durations on the Areas of Interests recorded by the eye-tracking device. We used various analysis techniques, including Mann-Whitney, regression, and Levenshtein distance, to investigate how confused users differed …