Characterizing Instructional Leader Interactions In A Social Learning Management System Using Social Network Analysis,
2019
Ateneo de Manila University
Characterizing Instructional Leader Interactions In A Social Learning Management System Using Social Network Analysis, Orven E. Llantos, Ma. Regina Justina E. Estuar
Department of Information Systems & Computer Science Faculty Publications
Online learning environments are designed with specific users and respective roles in mind. However, for social systems that thrive on the interaction between and among users, important features are developed based on relationships that evolve over time. Typical learning management systems are designed with the teacher and the student as primary users of the system. my.eskwela is a social learning management system that has been designed for use in public schools in the Philippines with the inclusion of an additional user, the school administrator. Although administrators influence on student learning through mediated effects of instructional leadership, pieces of literature are …
Estimating Glycemic Impact Of Cooking Recipes Via Online Crowdsourcing And Machine Learning,
2019
Singapore Management University
Estimating Glycemic Impact Of Cooking Recipes Via Online Crowdsourcing And Machine Learning, Helena Lee, Palakorn Achananuparp, Yue Liu, Ee-Peng Lim, Lav R. Varshney
Research Collection School Of Computing and Information Systems
Consumption of diets with low glycemic impact is highly recommended for diabetics and pre-diabetics as it helps maintain their blood glucose levels. However, laboratory analysis of dietary glycemic potency is time-consuming and expensive. In this paper, we explore a data-driven approach utilizing online crowdsourcing and machine learning to estimate the glycemic impact of cooking recipes. We show that a commonly used healthiness metric may not always be effective in determining recipes suitable for diabetics, thus emphasizing the importance of the glycemic-impact estimation task. Our best classification model, trained on nutritional and crowdsourced data obtained from Amazon Mechanical Turk (AMT), can …
Automated Theme Search In Ico Whitepapers,
2019
Singapore Management University
Automated Theme Search In Ico Whitepapers, Chuanjie Fu, Andrew Koh, Paul Griffin
Research Collection School Of Computing and Information Systems
The authors explore how topic modeling can be used to automate the categorization of initial coin offerings (ICOs) into different topics (e.g., finance, media, information, professional services, health and social, natural resources) based solely on the content within the whitepapers. This tool has been developed by fitting a latent Dirichlet allocation (LDA) model to the text extracted from the ICO whitepapers. After evaluating the automated categorization of whitepapers using statistical and human judgment methods, it is determined that there is enough evidence to conclude that the LDA model appropriately categorizes the ICO whitepapers. The results from a two-population proportion test …
Aspect And Opinion Aware Abstractive Review Summarization With Reinforced Hard Typed Decoder,
2019
Tsinghua University
Aspect And Opinion Aware Abstractive Review Summarization With Reinforced Hard Typed Decoder, Yufei Tian, Jianfei Yu, Jing Jiang
Research Collection School Of Computing and Information Systems
In this paper, we study abstractive review summarization. Observing that review summaries often consist of aspect words, opinion words and context words, we propose a two-stage reinforcement learning approach, which first predicts the output word type from the three types, and then leverages the predicted word type to generate the final word distribution. Experimental results on two Amazon product review datasets demonstrate that our method can consistently outperform several strong baseline approaches based on ROUGE scores.
Traceable Dynamic Public Auditing With Identity Privacy Preserving For Cloud Storage,
2019
Singapore Management University
Traceable Dynamic Public Auditing With Identity Privacy Preserving For Cloud Storage, Yinghui Zhang, Tiantian Zhang, Rui Guo, Shengmin Xu, Dong Zheng
Research Collection School Of Computing and Information Systems
In cloud computing era, an increasing number of resource-constrained users outsource their data to cloud servers. Due to the untrustworthiness of cloud servers, it is important to ensure the integrity of outsourced data. However, most of existing solutions still have challenging issues needing to be addressed, such as the identity privacy protection of users, the traceability of users, the supporting of dynamic user operations, and the publicity of auditing. In order to tackle these issues simultaneously, in this paper, we propose a traceable dynamic public auditing scheme with identity privacy preserving for cloud storage. In the proposed scheme, a single …
Low-Resource Name Tagging Learned With Weakly Labeled Data,
2019
Singapore Management University
Low-Resource Name Tagging Learned With Weakly Labeled Data, Yixin Cao, Zikun Hu, Tat-Seng Chua, Zhiyuan Liu, Heng Ji
Research Collection School Of Computing and Information Systems
Name tagging in low-resource languages or domains suffers from inadequate training data. Existing work heavily relies on additional information, while leaving those noisy annotations unexplored that extensively exist on the web. In this paper, we propose a novel neural model for name tagging solely based on weakly labeled (WL) data, so that it can be applied in any low-resource settings. To take the best advantage of all WL sentences, we split them into high-quality and noisy portions for two modules, respectively: (1) a classification module focusing on the large portion of noisy data can efficiently and robustly pretrain the tag …
Ad-Link: An Adaptive Approach For User Identity Linkage,
2019
Singapore Management University
Ad-Link: An Adaptive Approach For User Identity Linkage, Xin Mu, Wei Xie, Ka Wei, Roy Lee, Feida Zhu, Ee Peng Lim
Research Collection School Of Computing and Information Systems
User identity linkage (UIL) refers to linking accounts of the same user across different online social platforms. The state-of-the-art UIL methods usually perform account matching using user account’s features derived from the profile attributes, content and relationships. They are however static and do not adapt well to fast-changing online social data due to: (a) new content and activities generated by users; as well as (b) new platform functions introduced to users. In particular, the importance of features used in UIL methods may change over time and new important user features may be introduced. In this paper, we proposed AD-Link, a …
Automatic Generation Of Pull Request Descriptions,
2019
Zhejiang University
Automatic Generation Of Pull Request Descriptions, Zhongxin Liu, Xin Xia, Christoph Treude, David Lo, Shanping Li
Research Collection School Of Computing and Information Systems
Enabled by the pull-based development model, developers can easily contribute to a project through pull requests (PRs). When creating a PR, developers can add a free-form description to describe what changes are made in this PR and/or why. Such a description is helpful for reviewers and other developers to gain a quick understanding of the PR without touching the details and may reduce the possibility of the PR being ignored or rejected. However, developers sometimes neglect to write descriptions for PRs. For example, in our collected dataset with over 333K PRs, more than 34% of the PR descriptions are empty. …
Semi-Supervised Entity Alignment Via Joint Knowledge Embedding Model And Cross-Graph Model,
2019
Singapore Management University
Semi-Supervised Entity Alignment Via Joint Knowledge Embedding Model And Cross-Graph Model, Chengjiang Li, Yixin Cao, Lei Hou, Jiaxin Shi, Juanzi Li, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Entity alignment aims at integrating complementary knowledge graphs (KGs) from different sources or languages, which may benefit many knowledge-driven applications. It is challenging due to the heterogeneity of KGs and limited seed alignments. In this paper, we propose a semi-supervised entity alignment method by joint Knowledge Embedding model and Cross-Graph model (KECG). It can make better use of seed alignments to propagate over the entire graphs with KG-based constraints. Specifically, as for the knowledge embedding model, we utilize TransE to implicitly complete two KGs towards consistency and learn relational constraints between entities. As for the cross-graph model, we extend Graph …
Stylistic Features Usage: Similarities And Differences Using Multiple Social Networks,
2019
Singapore Management University
Stylistic Features Usage: Similarities And Differences Using Multiple Social Networks, Kholoud Khalil Aldous, Jisun An, Bernard J. Jansen
Research Collection School Of Computing and Information Systems
User engagement on social networks is essential for news outlets where they often distribute online content. News outlets simultaneously leverage multiple social media platforms to reach their overall audience and to increase marketshare. In this research, we analyze ten common stylistic features indicative of user engagement for news postings on multiple social media platforms. We display the stylistic features usage differences of news posts from various news sources. Results show that there are differences in the usage of stylistic features across social media platforms (Facebook, Instagram, Twitter, and YouTube). Online news outlets can benefit from these findings in building guidelines …
Special Issue On Multimedia Recommendation And Multi-Modal Data Analysis,
2019
Singapore Management University
Special Issue On Multimedia Recommendation And Multi-Modal Data Analysis, Xiangnan He, Zhenguang Liu, Hanwang Zhang, Chong-Wah Ngo, Svebor Karaman, Yongfeng Zhang
Research Collection School Of Computing and Information Systems
Rich multimedia contents are dominating the Web. In popular social media platforms such as FaceBook, Twitter, and Instagram, there are over millions of multimedia contents being created by users on a daily basis. In the meantime, multimedia data consist of data in multiple modalities, such as text, images, audio, and so on. Users are heavily overloaded by the massive multi-modal data, and it becomes critical to explore advanced techniques for heterogeneous big data analytics and multimedia recommendation. Traditional multimedia recommendation and data analysis technologies cannot well address the problem of understanding users’ preference in the feature-rich multimedia contents, and have …
Visualizing The Invisible: Occluded Vehicle Segmentation And Recovery,
2019
Singapore Management University
Visualizing The Invisible: Occluded Vehicle Segmentation And Recovery, Xiaosheng Yan, Feigege Wang, Wenxi Liu, Yuanlong Yu, Shengfeng He, Jia Pan
Research Collection School Of Computing and Information Systems
In this paper, we propose a novel iterative multi-task framework to complete the segmentation mask of an occluded vehicle and recover the appearance of its invisible parts. In particular, firstly, to improve the quality of the segmentation completion, we present two coupled discriminators that introduce an auxiliary 3D model pool for sampling authentic silhouettes as adversarial samples. In addition, we propose a two-path structure with a shared network to enhance the appearance recovery capability. By iteratively performing the segmentation completion and the appearance recovery, the results will be progressively refined. To evaluate our method, we present a dataset, Occluded Vehicle …
Medtruth: A Semi-Supervised Approach To Discovering Knowledge Condition Information From Multi-Source Medical Data,
2019
Singapore Management University
Medtruth: A Semi-Supervised Approach To Discovering Knowledge Condition Information From Multi-Source Medical Data, Yang Deng, Yaliang Li, Ying Shen, Nan Du, Wei Fan, Min Yang, Kai Lei
Research Collection School Of Computing and Information Systems
Knowledge Graph (KG) contains entities and the relations between entities. Due to its representation ability, KG has been successfully applied to support many medical/healthcare tasks. However, in the medical domain, knowledge holds under certain conditions. Such conditions for medical knowledge are crucial for decisionmaking in various medical applications, which is missing in existing medical KGs. In this paper, we aim to discovery medical knowledge conditions from texts to enrich KGs. Electronic Medical Records (EMRs) are systematized collection of clinical data and contain detailed information about patients, thus EMRs can be a good resource to discover medical knowledge conditions. Unfortunately, the …
Data Curation Workshop: Tips And Tools For Today,
2019
Miami University
Data Curation Workshop: Tips And Tools For Today, Matthew M. Benzing
Charleston Library Conference
The current state of research data is like a disorganized photo collection: a mix of formats scattered across different media without a lot of authority control. That is changing as the need to make data available to researchers across the world is becoming recognized. Researchers know that their data needs to be maintained and made accessible, but often they do not have the time or the inclination to get involved in all of the details. This provides an excellent opportunity for librarians. Data curation is the process of preparing data to be made available in a repository with the goal …
On Finding Two Posets That Cover Given Linear Orders,
2019
University of the Philippines Diliman
On Finding Two Posets That Cover Given Linear Orders, Ivy Ordanel, Proceso L. Fernandez Jr, Henry Adorna
Department of Information Systems & Computer Science Faculty Publications
The Poset Cover Problem is an optimization problem where the goal is to determine a minimum set of posets that covers a given set of linear orders. This problem is relevant in the field of data mining, specifically in determining directed networks or models that explain the ordering of objects in a large sequential dataset. It is already known that the decision version of the problem is NP-Hard while its variation where the goal is to determine only a single poset that covers the input is in P. In this study, we investigate the variation, which we call the 2-Poset …
Ml4iot: A Framework To Orchestrate Machine Learning Workflows On Internet Of Things Data,
2019
Western University
Ml4iot: A Framework To Orchestrate Machine Learning Workflows On Internet Of Things Data, Jose Miguel Alves, Leonardo Honorio, Miriam A M Capretz
Electrical and Computer Engineering Publications
Internet of Things (IoT) applications generate vast amounts of real-time data. Temporal analysis of these data series to discover behavioural patterns may lead to qualified knowledge affecting a broad range of industries. Hence, the use of machine learning (ML) algorithms over IoT data has the potential to improve safety, economy, and performance in critical processes. However, creating ML workflows at scale is a challenging task that depends upon both production and specialized skills. Such tasks require investigation, understanding, selection, and implementation of specific ML workflows, which often lead to bottlenecks, production issues, and code management complexity and even then may …
Factors Influencing Knowledge Transfer In Onshore Information Systems Outsourcing In Ethiopia,
2019
Addis Ababa University, Ethiopia
Factors Influencing Knowledge Transfer In Onshore Information Systems Outsourcing In Ethiopia, Solomon A. Nurye, Alem Molla, Temtim Assefa Desta
The African Journal of Information Systems
Knowledge transfer in onshore information systems (IS) outsourcing projects in Africa is an important but under-researched phenomenon. This study focuses on the client-vendor perspective and examines the factors that influence knowledge transfer in onshore information systems outsourcing in Ethiopia. Conceptually, knowledge-based perspectives of IS outsourcing is used to identify an initial set of factors to frame the empirical study. This is followed by semi-structured interviews with ten project managers. The findings indicate that five key factors, namely mutual absorptive capacity, mutual learning intent, mutual trust, mutual disseminative capacity and project staff turnover influence knowledge transfer in outsourced IS projects. The …
Automatic Fashion Knowledge Extraction From Social Media,
2019
Singapore Management University
Automatic Fashion Knowledge Extraction From Social Media, Yunshan Ma, Lizi Liao, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Fashion knowledge plays a pivotal role in helping people in their dressing. In this paper, we present a novel system to automatically harvest fashion knowledge from social media. It unifies three tasks of occasion, person and clothing discovery from multiple modalities of images, texts and metadata. A contextualized fashion concept learning model is applied to leverage the rich contextual information for improving the fashion concept learning performance. At the same time, to counter the label noise within training data, we employ a weak label modeling method to further boost the performance. We build a website to demonstrate the quality of …
Knowledge Base Question Answering With A Matching-Aggregation Model And Question-Specific Contextual Relations,
2019
Singapore Management University
Knowledge Base Question Answering With A Matching-Aggregation Model And Question-Specific Contextual Relations, Yunshi Lan, Shuohang Wang, Jing Jiang
Research Collection School Of Computing and Information Systems
Making use of knowledge bases to answer questions (KBQA) is a key direction in question answering systems. Researchers have developed a diverse range of methods to address this problem, but there are still some limitations with the existing methods. Specifically, the existing neural network-based methods for KBQA have not taken advantage of the recent “matching-aggregation” framework for the sequence matching, and when representing a candidate answer entity, they may not choose the most useful context of the candidate for matching. In this paper, we explore the use of a “matching-aggregation” framework to match candidate answers with questions. We further make …
Smartbfa: A Passive Crowdsourcing System For Point-To-Point Barrier-Free Access,
2019
Singapore Management University
Smartbfa: A Passive Crowdsourcing System For Point-To-Point Barrier-Free Access, Mohammed Nazir Kamaldin, Susan Kee, Songwei Kong, Chengkai Lee, Huiguang Liang, Alisha Saini, Hwee-Pink Tan, Hwee Xian Tan
Research Collection School Of Computing and Information Systems
At the Bloomberg Live `Sooner Than You Think' forum [1] held in Singapore in 2018, nearly 75% of delegates picked inclusiveness to be the key measure of success for a smart city. An inclusive smart city is a citizen-centered approach that extends the experiences provided by smart city solutions to all citizens, including seniors and persons with disabilities (PwDs).Despite existing regulations on barrier-free accessibility for buildings and public infrastructure, pedestrian infrastructure is generally still inaccessible to PwDs in many parts of the world. In this paper, we present SmartBFA (Smart Mobility and Accessibility for Barrier Free Access) - a publicly-funded …
