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Articles 4261 - 4290 of 8481
Full-Text Articles in Computer Sciences
The Role Of Urban Mobility In Retail Business Survival, Krittika D'Silva, Kasthuri Jayarajah, Anastasios Noulas, Cecilia Mascolo, Archan Misra
The Role Of Urban Mobility In Retail Business Survival, Krittika D'Silva, Kasthuri Jayarajah, Anastasios Noulas, Cecilia Mascolo, Archan Misra
Research Collection School Of Computing and Information Systems
Economic and urban planning agencies have strong interest in tackling the hard problem of predicting the odds of survival of individual retail businesses. In this work, we tap urban mobility data available both from a location-based intelligence platform, Foursquare, and from public transportation agencies, and investigate whether mobility-derived features can help foretell the failure of such retail businesses, over a 6 month horizon, across 10 distinct cities spanning the globe. We hypothesise that the survival of such a retail outlet is correlated with not only venue-specific characteristics but also broader neighbourhood-level effects. Through careful statistical analysis of Foursquare and taxi …
Domain-Specific Cross-Language Relevant Question Retrieval, Bowen Xu, Zhenchang Xing, Xin Xia, David Lo, Shanping Li
Domain-Specific Cross-Language Relevant Question Retrieval, Bowen Xu, Zhenchang Xing, Xin Xia, David Lo, Shanping Li
Research Collection School Of Computing and Information Systems
Chinese developers often cannot effectively search questions in English, because they may have difficulties in translating technical words from Chinese to English and formulating proper English queries. For the purpose of helping Chinese developers take advantage of the rich knowledge base of Stack Overflow and simplify the question retrieval process, we propose an automated cross-language relevant question retrieval (CLRQR) system to retrieve relevant English questions for a given Chinese question. CLRQR first extracts essential information (both Chinese and English) from the title and description of the input Chinese question, then performs domain-specific translation of the essential Chinese information into English, …
A Novel Representation And Compression For Queries On Trajectories In Road Networks, Xiaochun Yang, Bin Wang, Kai Yang, Chengfei Liu, Baihua Zheng
A Novel Representation And Compression For Queries On Trajectories In Road Networks, Xiaochun Yang, Bin Wang, Kai Yang, Chengfei Liu, Baihua Zheng
Research Collection School Of Computing and Information Systems
Recording and querying time-stamped trajectories incurs high cost of data storage and computing. In this paper, we explore several characteristics of the trajectories in road mbox{networks}, which have motivated the idea of coding trajectories by associating timestamps with relative spatial path and locations. Such a representation contains large number of duplicate information to achieve a lower entropy compared with the existing representations, thereby drastically cutting the storage cost. We propose several techniques to compress spatial path and locations separately, which can support fast positioning and achieve better compression ratio. For locations, we propose two novel encoding schemes such that the …
Fast And Robust Segmentation Of White Blood Cell Images By Self-Supervised Learning, Xin Zheng, Yong Wang, Guoyou Wang, Jianguo Liu
Fast And Robust Segmentation Of White Blood Cell Images By Self-Supervised Learning, Xin Zheng, Yong Wang, Guoyou Wang, Jianguo Liu
Research Collection School Of Computing and Information Systems
A fast and accurate white blood cell (WBC) segmentation remains a challenging task, as different WBCs vary significantly in color and shape due to cell type differences, staining technique variations and the adhesion between the WBC and red blood cells. In this paper, a self-supervised learning approach, consisting of unsupervised initial segmentation and supervised segmentation refinement, is presented. The first module extracts the overall foreground region from the cell image by K-means clustering, and then generates a coarse WBC region by touching-cell splitting based on concavity analysis. The second module further uses the coarse segmentation result of the first module …
A Utp Semantics For Communicating Processes With Shared Variables And Its Formal Encoding In Pvs, Ling Shi, Yongxin Zhao, Yang Liu, Jun Sun, Jin Song Dong, Shengchao Qin
A Utp Semantics For Communicating Processes With Shared Variables And Its Formal Encoding In Pvs, Ling Shi, Yongxin Zhao, Yang Liu, Jun Sun, Jin Song Dong, Shengchao Qin
Research Collection School Of Computing and Information Systems
CSP# (communicating sequential programs) is a modelling language designed for specifying concurrent systems by integrating CSP-like compositional operators with sequential programs updating shared variables. In this work, we define an observation-oriented denotational semantics in an open environment for the CSP# language based on the UTP framework. To deal with shared variables, we lift traditional event-based traces into mixed traces which consist of state-event pairs for recording process behaviours. To capture all possible concurrency behaviours between action/channel-based communications and global shared variables, we construct a comprehensive set of rules on merging traces from processes which run in parallel/interleaving. We also define …
Pageflip: Leveraging Page-Flipping Gestures For Efficient Command And Value Selection On Smartwatches, Teng Han, Jiannan Li, Khalad Hasan, Keisuke Nakamura, Randy Gomez, Ravin Balakrishnan, Pourang Irani
Pageflip: Leveraging Page-Flipping Gestures For Efficient Command And Value Selection On Smartwatches, Teng Han, Jiannan Li, Khalad Hasan, Keisuke Nakamura, Randy Gomez, Ravin Balakrishnan, Pourang Irani
Research Collection School Of Computing and Information Systems
Selecting an item of interest on smartwatches can be tedious and time-consuming as it involves a series of swipe and tap actions. We present PageFlip, a novel method that combines into a single action multiple touch operations such as command invocation and value selection for efficient interaction on smartwatches. PageFlip operates with a page flip gesture that starts by dragging the UI from a corner of the device. We first design PageFlip by examining its key design factors such as corners, drag directions and drag distances. We next compare PageFlip to a functionally equivalent radial menu and a standard swipe …
'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 …
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 …
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 …
Sok: Towards The Science Of Security And Privacy In Machine Learning, Nicolas Papernot, Patrick Mcdaniel, Arunesh Sinha, Michael Wellman
Sok: Towards The Science Of Security And Privacy In Machine Learning, Nicolas Papernot, Patrick Mcdaniel, Arunesh Sinha, Michael Wellman
Research Collection School Of Computing and Information Systems
Advances in machine learning (ML) in recent years have enabled a dizzying array of applications such as data analytics, autonomous systems, and security diagnostics. ML is now pervasive—new systems and models are being deployed in every domain imaginable, leading to rapid and widespread deployment of software based inference and decision making. There is growing recognition that ML exposes new vulnerabilities in software systems, yet the technical community’s understanding of the nature and extent of these vulnerabilities remains limited. We systematize recent findings on ML security and privacy, focusing on attacks identified on these systems and defenses crafted to date. We …
Pccf: Periodic And Continual Temporal Co-Factorization For Recommender Systems, Guibing Guo, Feida Zhu, Shilin Qu, Xingwei Wang
Pccf: Periodic And Continual Temporal Co-Factorization For Recommender Systems, Guibing Guo, Feida Zhu, Shilin Qu, Xingwei Wang
Research Collection School Of Computing and Information Systems
Rating-only collaborative filtering has been extensively studied for decades with great improvements achieved in predicting a user’s preference on a target item at a particular time point. Yet, it remains a research challenge on how to capture users’ rating patterns which may drift over time. In this article, we propose a time-aware matrix co-factorization model, called PCCF, which considers two types of temporal effects, i.e., periodic and continual. Specifically, periodic effects refer to the impact of discrete periodic time slices with which users’ preferences may be associated, and continual effects refer to the impact of continuous gradual time over which …
Modeling Security And Privacy Requirements: A Use Case-Driven Approach, Phu Xuan Mai, Arda Goknil, Lwin Khin Shar, Fabrizio Pastore, Lionel Briand, Shaban Shaame
Modeling Security And Privacy Requirements: A Use Case-Driven Approach, Phu Xuan Mai, Arda Goknil, Lwin Khin Shar, Fabrizio Pastore, Lionel Briand, Shaban Shaame
Research Collection School Of Computing and Information Systems
Context: Modern internet-based services, ranging from food-delivery to home-caring, leverage the availability of multiple programmable devices to provide handy services tailored to end-user needs. These services are delivered through an ecosystem of device-specific software components and interfaces (e.g., mobile and wearable device applications). Since they often handle private information (e.g., location and health status), their security and privacy requirements are of crucial importance. Defining and analyzing those requirements is a significant challenge due to the multiple types of software components and devices integrated into software ecosystems. Each software component presents peculiarities that often depend on the context and the devices …
Empirical Study Of Face Authentication Systems Under Osnfd Attacks, Yan Li, Yingjiu Li, Xu, Ke, Qiang Yan, Robert H. Deng
Empirical Study Of Face Authentication Systems Under Osnfd Attacks, Yan Li, Yingjiu Li, Xu, Ke, Qiang Yan, Robert H. Deng
Research Collection School Of Computing and Information Systems
Face authentication has been widely available on smartphones, tablets, and laptops. As numerous personal images are published in online social networks (OSNs), OSN-based facial disclosure (OSNFD) creates significant threat against face authentication. We make the first attempt to quantitatively measure OSNFD threat to real-world face authentication systems on smartphones, tablets, and laptops. Our results show that the percentage of vulnerable users that are subject to spoofing attacks is high, which is about 64% for laptop users, and 93% smartphone/tablet users. We investigate liveness detection methods in the real-world face authentication systems against OSNFD threat. We discover that under protection of …
Criteria-Based Encryption, Tran Viet Xuan Phuong, Guomin Yang, Willy Susilo
Criteria-Based Encryption, Tran Viet Xuan Phuong, Guomin Yang, Willy Susilo
Research Collection School Of Computing and Information Systems
We present a new type of public-key encryption called Criteria-based Encryption (or , for short). Different from Attribute-based Encryption, in , we consider the access policies as criteria carrying different weights. A user must hold some cases (or answers) satisfying the criteria and have sufficient weights in order to successfully decrypt a message. We then propose two Schemes under different settings: the first scheme requires a user to have at least one case for a criterion specified by the encryptor in the access structure, while the second scheme requires a user to have all the cases for each criterion. We …
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) …
Every Step You Take, I’Ll Be Watching You: Practical Stepauth-Entication Of Rfid Paths, Kai Bu, Yingjiu Li
Every Step You Take, I’Ll Be Watching You: Practical Stepauth-Entication Of Rfid Paths, Kai Bu, Yingjiu Li
Research Collection School Of Computing and Information Systems
Path authentication thwarts counterfeits in RFID-based supply chains. Its motivation is that tagged products taking invalid paths are likely faked and injected by adversaries at certain supply chain partners/steps. Existing solutions are path-grained in that they simply regard a product as genuine if it takes any valid path. Furthermore, they enforce distributed authentication by offloading the sets of valid paths to some or all steps from a centralized issuer. This not only imposes network and storage overhead but also leaks transaction privacy. We present StepAuth, the first step-grained path authentication protocol that is practically efficient for authenticating products with strict …
Octopus: An Online Topic-Aware Influence Analysis System For Social Networks, Ju Fan, Jiarong Qiu, Yuchen Li, Qingfei Meng, Dongxiang Zhang, Guoliang Li, Kian-Lee Tan, Xiaoyong Du
Octopus: An Online Topic-Aware Influence Analysis System For Social Networks, Ju Fan, Jiarong Qiu, Yuchen Li, Qingfei Meng, Dongxiang Zhang, Guoliang Li, Kian-Lee Tan, Xiaoyong Du
Research Collection School Of Computing and Information Systems
The wide adoption of social networks has brought a new demand on influence analysis. This paper presents OCTOPUS that offers social network users and analysts valuable insights through topic-aware social influence analysis services. OCTOPUS has the following novel features. First, OCTOPUS provides a user-friendly interface that allows users to employ simple and easy-to-use keywords to perform influence analysis. Second, OCTOPUS provides three powerful keyword-based topic-aware influence analysis tools: keyword-based influential user discovery, personalized influential keywords suggestion, and interactive influential paths exploration. These tools can not only discover influential users, but also provide insights on how the users influence the network. …
Augmented Keyword Search On Spatial Entity Databases, Dongxiang Zhang, Yuchen Li, Xin Cao, Jie Shao, Heng Tao Shen
Augmented Keyword Search On Spatial Entity Databases, Dongxiang Zhang, Yuchen Li, Xin Cao, Jie Shao, Heng Tao Shen
Research Collection School Of Computing and Information Systems
In this paper, we propose a new type of query that augments the spatial keyword search with an additional boolean expression constraint. The query is issued against a corpus of structured or semi-structured spatial entities and is very useful in applications like mobile search and targeted location-aware advertising. We devise three types of indexing and filtering strategies. First, we utilize the hybrid IR2" role="presentation" style="display: inline; line-height: normal; letter-spacing: normal; word-spacing: normal; word-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border-width: 0px; border-style: initial; position: relative;">IR2IR2-tree and propose a novel hashing …
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 …
Introducing Basic Programming To Pre-University Students: A Successful Initiative In Singapore, Heng Ngee Mok, Vandana Ramachandra Rao
Introducing Basic Programming To Pre-University Students: A Successful Initiative In Singapore, Heng Ngee Mok, Vandana Ramachandra Rao
Research Collection School Of Computing and Information Systems
“Let’s Code!” is an intensive 3-week basic programming course that aims to formally expose pre-university students in Singapore to programming. This course was conducted in blended-learning format, and included lecture videos, self-check quizzes, video conferences, meet-up tutorials and take-home programming assignments. The authors hope to capture the experience gained from running this course for educators who intend to implement similar courses in the future. Besides a detailed description of this course, significant changes that were made based on feedback from participants and members of the teaching team are documented here.
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 …
A Feasibility Study On Crowdsourcing To Monitor Municipal Resources In Smart Cities, Thivya Kandappu, Archan Misra, Ming Hui, Desmond (Xu Minghui) Koh, Randy Tandriansyah Daratan, Nikita Jaiman
A Feasibility Study On Crowdsourcing To Monitor Municipal Resources In Smart Cities, Thivya Kandappu, Archan Misra, Ming Hui, Desmond (Xu Minghui) Koh, Randy Tandriansyah Daratan, Nikita Jaiman
Research Collection School Of Computing and Information Systems
Active citizenry, whereby citizens actively participate inreporting and addressing challenges in urban service delivery is a strategic goalof smart cities such as Singapore. In spite of the promise, we believe that thesuccess of such large-scale nation-wide crowdsourcing deployments depend on thereal-word user preferences and behavioral characteristics of citizens. In thispaper, we first present our findings on behavioral preferences and key concernsof citizens regarding smart-city services via an opinion survey conducted with 1300participants. We then propose a “citizen-controlled” urban services reportingplatform where citizens actively report on the status of various municipalresources. We advocate the importance of matching user mobility patternsagainst task …
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, …
Entagrec(++): An Enhanced Tag Recommendation System For Software Information Sites, Shawei Wang, David Lo, Bogdan Vasilescu, Alexander Serebrenik
Entagrec(++): An Enhanced Tag Recommendation System For Software Information Sites, Shawei Wang, David Lo, Bogdan Vasilescu, Alexander Serebrenik
Research Collection School Of Computing and Information Systems
Software engineers share experiences with modern technologies using 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. Tags help to improve the organization of questions and simplify the browsing of questions for users. However, tags assigned to objects tend to be noisy and some objects are not well tagged. For instance, 14.7% of the questions that were posted in 2015 on Stack Overflow needed tag re-editing after the initial assignment. To improve the quality of tags in software information sites, we propose EnTagRec …
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, …
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 help developers better allocate 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 past history of buggy classes. These techniques work well as long as a sufficient amount of data is available to train a prediction model. However, there is rarely enough training data for new software projects. To deal with this problem, cross-project defect prediction, which transfers a prediction model trained using data from one project to another, has been proposed and is regarded as …
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, …
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, …