A Framework For Identifying Host-Based Artifacts In Dark Web Investigations,
2020
Dakota State University
A Framework For Identifying Host-Based Artifacts In Dark Web Investigations, Arica Kulm
Masters Theses & Doctoral Dissertations
The dark web is the hidden part of the internet that is not indexed by search engines and is only accessible with a specific browser like The Onion Router (Tor). Tor was originally developed as a means of secure communications and is still used worldwide for individuals seeking privacy or those wanting to circumvent restrictive regimes. The dark web has become synonymous with nefarious and illicit content which manifests itself in underground marketplaces containing illegal goods such as drugs, stolen credit cards, stolen user credentials, child pornography, and more (Kohen, 2017). Dark web marketplaces contribute both to illegal drug usage …
Cost-Sensitive Deep Forest For Price Prediction,
2020
Singapore Management University
Cost-Sensitive Deep Forest For Price Prediction, Chao Ma, Zhenbing Liu, Zhiguang Cao, Wen Song, Jie Zhang, Weiliang Zeng
Research Collection School Of Computing and Information Systems
For many real-world applications, predicting a price range is more practical and desirable than predicting a concrete value. In this case, price prediction can be regarded as a classification problem. Although deep forest is recognized as the best solution to many classification problems, a crucial issue limits its direct application to price prediction, i.e., it treated all the misclassifications equally no matter how far away they are from the real classes, since their impacts on the accuracy are the same. This is unreasonable to price prediction as the misclassification should be as close to the real price range as possible …
Capitalising Product Associations In A Supermarket Retail Environment,
2020
Singapore Management University
Capitalising Product Associations In A Supermarket Retail Environment, Michelle L. F. Cheong, Yong Qing Chia
Research Collection School Of Computing and Information Systems
This paper explores methods to capitalise on retail companies’ transactional databases, to mine meaningful product associations, and to design product placement strategies as a means to drive sales. We implemented three in-store initiatives based on our hypotheses – placing products with high associations together will induce an increase in sales of consequent; introducing an antecedent that is new to store will bring about a similar impact on sales of consequent based on established product association rules uncovered from other stores. Sales tracking over twelve weeks revealed that there were improvements in sales of consequents across all three initiatives performed in-store.
Exploring And Evaluating Attributes, Values, And Structures For Entity Alignment,
2020
Singapore Management University
Exploring And Evaluating Attributes, Values, And Structures For Entity Alignment, Zhiyuan Liu, Yixin Cao, Liangming Pan, Juanzi Li, Zhiyuan Liu, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Entity alignment (EA) aims at building a unified Knowledge Graph (KG) of rich content by linking the equivalent entities from various KGs. GNN-based EA methods present promising performance by modeling the KG structure defined by relation triples. However, attribute triples can also provide crucial alignment signal but have not been well explored yet. In this paper, we propose to utilize an attributed value encoder and partition the KG into subgraphs to model the various types of attribute triples efficiently. Besides, the performances of current EA methods are overestimated because of the name-bias of existing EA datasets. To make an objective …
Efficient And Fair Data Valuation For Horizontal Federated Learning,
2020
Singapore Management University
Efficient And Fair Data Valuation For Horizontal Federated Learning, Shuyue Wei, Yongxin Tong, Zimu Zhou, Tianshu Song
Research Collection School Of Computing and Information Systems
Availability of big data is crucial for modern machine learning applications and services. Federated learning is an emerging paradigm to unite different data owners for machine learning on massive data sets without worrying about data privacy. Yet data owners may still be reluctant to contribute unless their data sets are fairly valuated and paid. In this work, we adapt Shapley value, a widely used data valuation metric to valuating data providers in federated learning. Prior data valuation schemes for machine learning incur high computation cost because they require training of extra models on all data set combinations. For efficient data …
A Survey Of Typical Attributed Graph Queries,
2020
Singapore Management University
A Survey Of Typical Attributed Graph Queries, Yanhao Wang, Yuchen Li, Ju Fan, Chang Ye, Mingke Chai
Research Collection School Of Computing and Information Systems
Graphs are commonly used for representing complex structures such as social relationships, biological interactions, and knowledge bases. In many scenarios, graphs not only represent topological relationships but also store the attributes that denote the semantics associated with their vertices and edges, known as attributed graphs. Attributed graphs can meet demands for a wide range of applications, and thus a variety of queries on attributed graphs have been proposed. However, these diverse types of attributed graph queries have not been systematically investigated yet. In this paper, we provide an extensive survey of several typical types of attributed graph queries. We propose …
Answerfact: Fact Checking In Product Question Answering,
2020
Singapore Management University
Answerfact: Fact Checking In Product Question Answering, Wenxuan Zhang, Yang Deng, Jing Ma, Wai Lam
Research Collection School Of Computing and Information Systems
Product-related question answering platforms nowadays are widely employed in many E-commerce sites, providing a convenient way for potential customers to address their concerns during online shopping. However, the misinformation in the answers on those platforms poses unprecedented challenges for users to obtain reliable and truthful product information, which may even cause a commercial loss in E-commerce business. To tackle this issue, we investigate to predict the veracity of answers in this paper and introduce AnswerFact, a large scale fact checking dataset from product question answering forums. Each answer is accompanied by its veracity label and associated evidence sentences, providing a …
Cache-Based Optimization For Block Commit Of Hyperledger Fabric,
2020
Singapore Management University
Cache-Based Optimization For Block Commit Of Hyperledger Fabric, Qinqi Xu, Yimin Lin, Qingshan Jiang, Mengqiu Zhang
Research Collection Lee Kong Chian School Of Business
Blockchain technology has been applied to various domains in recent years, and Hyperledger Fabric is one of the most popular blockchain systems. This paper conducts a fine analysis on the block commit of Hyperledger Fabric through latency evaluation as well as flame graph. To overcome the bottlenecks pointed out by the analysts, this paper proposes two cache-based schemata. In particular, we add a cache for index and state storage to accelerate commit. We also cache deserialized block globally for block delivery to avoid repeat operations. The experiments reveal performance improvement of 2×. Notably, our optimizations can also be implemented easily …
Exploring The Impact Of Covid-19 On Aviation Industry: A Text Mining Approach,
2020
Singapore Management University
Exploring The Impact Of Covid-19 On Aviation Industry: A Text Mining Approach, Gottipati Swapna, Kyong Jin Shim, Weiling Angeline Jiang, Sheng Wei Andre Justin Lee
Research Collection School Of Computing and Information Systems
Our study presents a comprehensive analysis of news articles from FlightGlobal website during the first half of 2020. Our analyses reveal useful insights on themes and trends concerning the aviation industry during the COVID-19 period. We applied text mining and NLP techniques to analyse the articles for extracting the aviation themes and article sentiments (positive and negative). Our results show that there is a variation in the sentiment trends for themes aligned with the real-world developments of the pandemic. The article sentiment analysis can offer industry players a quick sense of the nature of developments in the industry. Our article …
Cross-Thought For Sentence Encoder Pre-Training,
2020
Singapore Management University
Cross-Thought For Sentence Encoder Pre-Training, Shuohang Wang, Yuwei Fang, Siqi Sun, Zhe Gan, Yu Cheng, Jingjing Liu, Jing Jiang
Research Collection School Of Computing and Information Systems
In this paper, we propose Cross-Thought, a novel approach to pre-training sequence encoder, which is instrumental in building reusable sequence embeddings for large-scale NLP tasks such as question answering. Instead of using the original signals of full sentences, we train a Transformer-based sequence encoder over a large set of short sequences, which allows the model to automatically select the most useful information for predicting masked words. Experiments on question answering and textual entailment tasks demonstrate that our pre-trained encoder can outperform state-of-the-art encoders trained with continuous sentence signals as well as traditional masked language modeling baselines. Our proposed approach also …
Coupled Hierarchical Transformer For Stance-Aware Rumor Verification In Social Media Conversations,
2020
Singapore Management University
Coupled Hierarchical Transformer For Stance-Aware Rumor Verification In Social Media Conversations, Jianfei Yu, Jing Jiang, Ling Min Serena Khoo, Hai Leong Chieu, Rui Xia
Research Collection School Of Computing and Information Systems
The prevalent use of social media enables rapid spread of rumors on a massive scale, which leads to the emerging need of automatic rumor verification (RV). A number of previous studies focus on leveraging stance classification to enhance RV with multi-task learning (MTL) methods. However, most of these methods failed to employ pre-trained contextualized embeddings such as BERT, and did not exploit inter-task dependencies by using predicted stance labels to improve the RV task. Therefore, in this paper, to extend BERT to obtain thread representations, we first propose a Hierarchical Transformer1 , which divides each long thread into shorter subthreads, …
Leveraging Profanity For Insincere Content Detection: A Neural Network Approach,
2020
Singapore Management University
Leveraging Profanity For Insincere Content Detection: A Neural Network Approach, Swapna Gottipati, Annabel Tan, David Jing Shan Chow, Joel Wee Kiat Lim
Research Collection School Of Computing and Information Systems
Community driven social media sites are rich sources of knowledge and entertainment and at the same vulnerable to the flames or toxic content that can be dangerous to various users of these platforms as well as to the society. Therefore, it is crucial to identify and remove such content to have a better and safe online experience. Manually eliminating flames is tedious and hence many research works focus on machine learning or deep learning models for automated methods. In this paper, we primarily focus on detecting the insincere content using neural network-based learning methods. We also integrated the profanity features …
Learning Personal Conscientiousness From Footprints In E-Learning Systems,
2020
National Cheng Kung University
Learning Personal Conscientiousness From Footprints In E-Learning Systems, Lo Pang-Yun Ting, Shan Yun Teng, Kun Ta Chuang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Personality inference has received widespread attention for its potential to infer psychological well being, job satisfaction, romantic relationship success, and professional performance. In this research, we focus on Conscientiousness, one of the well studied Big Five personality traits, which determines if a person is self-disciplined, organized, and hard-working. Research has shown that Conscientiousness is related to a person's academic and workplace success. For an expert to evaluate a person's Conscientiousness, long-term observation of the person's behavior at work place or at home is usually required. To reduce this evaluation effort as well as to cope with the increasing trend of …
How Should We Understand The Digital Economy In Asia? Critical Assessment And Research Agenda,
2020
Nankai University
How Should We Understand The Digital Economy In Asia? Critical Assessment And Research Agenda, Kai Li, Dan J. Kim, Karl R. Lang, Robert J. Kauffman, Maurizio Naldi
Research Collection School Of Computing and Information Systems
By Asian digital economy, we refer to high-tech developments, business and social transformations, and information-driven changes in the region's growth. We discuss its background and foundations, significance in Asia and contribution to removal of historical barriers in traditional business. We assess how new value chains are transforming country-level involvement in worldwide manufacturing and note "smiling curve theory" predictions about the global value chain in Asia for high-tech firms and their economies. The takeaway is that the digital economy in Asian nations involves revamping business processes through technology innovation, government policies for growth, and digital entrepreneurship. We analyze the "digital economy …
Empowering Singapore’S Smes: Fintech P2p Lending — A Lifeline For Smes’ Survival?,
2020
Singapore Management University
Empowering Singapore’S Smes: Fintech P2p Lending — A Lifeline For Smes’ Survival?, Grace Lee, Alan Megargel
Research Collection School Of Computing and Information Systems
The COVID-19 pandemic has sent shock waves throughout the world, pushed countries into lockdown, and wreaked havoc on the world’s people and the global economy. The damage to economies around the world caused by the COVID-19 pandemic has far exceeded that of the global financial crisis. While all businesses suffered hugely, it would be of grave consequence if the small and medium-sized enterprises (SMEs), an important segment of every country’s economy, are unable to withstand the shock wave and sustain themselves beyond this pandemic. The COVID-19 pandemic has highlighted the importance of cash flow or working capital for the viability …
Multi-Hop Inference For Question-Driven Summarization,
2020
Singapore Management University
Multi-Hop Inference For Question-Driven Summarization, Yang Deng, Wenxuan Zhang, Wai Lam
Research Collection School Of Computing and Information Systems
Question-driven summarization has been recently studied as an effective approach to summarizing the source document to produce concise but informative answers for non-factoid questions. In this work, we propose a novel question-driven abstractive summarization method, Multi-hop Selective Generator (MSG), to incorporate multi-hop reasoning into question-driven summarization and, meanwhile, provide justifications for the generated summaries. Specifically, we jointly model the relevance to the question and the interrelation among different sentences via a human-like multi-hop inference module, which captures important sentences for justifying the summarized answer. A gated selective pointer generator network with a multi-view coverage mechanism is designed to integrate diverse …
Covid-19 Pandemic – Online Education In The New Normal And The Next Normal,
2020
Singapore Management University
Covid-19 Pandemic – Online Education In The New Normal And The Next Normal, X. Xie, Keng Siau, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
The development and advancement of information technology provide a technical platform for education reform and opportunities for innovation in education. The global COVID-19 pandemic has created a new normal that further springboards such opportunities to large scale implementation of online education. Because online education has the advantages of flexibility, information accessibility, global reach, equity, innovation, and efficiency, a growing number of educational institutions are offering degree-granting distance and hybrid education programs. However, online education also has its shortcomings, which include technological constraints, the lack of a sense of belonging and connectedness, the presence of distractions, and a lack of engagement. …
The Role Of Information And Knowledge Of Weather Warnings In Marine Access Behavior : A Field Experiment In Coastal Area Of Bangladesh,
2020
Lingnan University
The Role Of Information And Knowledge Of Weather Warnings In Marine Access Behavior : A Field Experiment In Coastal Area Of Bangladesh, Khan Mehedi Hasan
Lingnan Theses (MPhil & PhD)
The world’s largest mangrove forest named Sundarban is located in the Bay of Bengal. Due to richness of aqua and forest resources, the coastal community of Khulna district of Bangladesh immensely depends on the forest for income and livelihoods, all the year round. For extracting resources, thousands of people enter into the forest by crossing river, generally with small boats. The region faces various natural disasters repeatedly. Each year about 13-14 cyclones are formed in the Bay of Bengal, which are threats for coastal households. Those hazards bear more risk for marine entrants. Analyzing coastal households’ marine access for two …
Privacy And The Digital Divide: Investigating Strategies For Digital Safety By People Of Color,
2020
Illinois State University
Privacy And The Digital Divide: Investigating Strategies For Digital Safety By People Of Color, Denavious Hoover
Theses and Dissertations
People of color are becoming increasingly concerned with digital privacy. They are concerned about the obfuscated data collection and sharing practices of major social media plat- forms and the strong entitlement of other users in the online space to their content. This study examines how people of color conceptualize and behave to produce safety in the online space, or, in other words, digital privacy. This study challenges notions that people are not purposeful about privacy in the online space and highlights the voices of people of color, whom are not of- ten included in theorizing or decision making about the …
Espade: An Efficient And Semantically Secure Shortest Path Discovery For Outsourced Location-Based Services,
2020
Montclair State University
Espade: An Efficient And Semantically Secure Shortest Path Discovery For Outsourced Location-Based Services, Bharath K. Samanthula, Divyadharshini Karthikeyan, Boxiang Dong, K. Anitha Kumari
Department of Computer Science Faculty Scholarship and Creative Works
With the rapid growth of smart devices and technological advancements in tracking geospatial data, the demand for Location-Based Services (LBS) is facing a constant rise in several domains, including military, healthcare and transportation. It is a natural step to migrate LBS to a cloud environment to achieve on-demand scalability and increased resiliency. Nonetheless, outsourcing sensitive location data to a third-party cloud provider raises a host of privacy concerns as the data owners have reduced visibility and control over the outsourced data. In this paper, we consider outsourced LBS where users want to retrieve map directions without disclosing their location information. …
