Regularizing Matrix Factorization with User and Item Embeddings for Recommendation

Following recent successes in exploiting both latent factor and word embedding models in recommendation, we propose a novel Regularized Multi-Embedding (RME) based recommendation model that simultaneously encapsulates the following ideas via decomposition: (1) which items a user likes, (2) which two users co-like the same items, (3) which two items users often co-liked, and (4) which two items users often co-disliked. In experimental validation, the RME outperforms competing state-of-the-art models in both explicit and implicit feedback datasets, significantly improving Recall@5 by 5.9~7.0%, NDCG@20 by 4.3~5.6%, and MAP@10 by 7.9~8.9%. In addition, under the cold-start scenario for users with the lowest number of interactions, against the competing models, the RME outperforms NDCG@5 by 20.2% and 29.4% in MovieLens-10M and MovieLens-20M datasets, respectively. Our datasets and source code are available at: https://github.com/thanhdtran/RME.git.Comment: CIKM 201

Understanding Price Rigidity On The Internet: A Massive Quasi-Experimental Data Mining Approach

This research is a three-essay dissertation for theory development and empirical research on price rigidity in e-commerce. Price rigidity involves prices that do not change with the regularity predicted by standard economic theory. The first essay is a case study exploring daily patterns of Internet pricing for the two major online bookstores, Amazon.com and Barnes and Noble.com at a micro-level analysis, informing our understanding of “how rigid prices are on the Internet.” The second essay proposes and evaluates an Internet-based price rigidity model to predict what variables can explain the observed empirical regularities and variations in price adjustment patterns of Internet-based retailers. Finally, the third essay investigates the practical importance of price points on the Internet and provides a rational choice explanation, based on “rational inattention theory.” I also provide additional commentary on a new empirical research approach called the massive quasi-experimental data mining method, which employs time-series data to examine price adjustment patterns and price rigidity on the Internet. Taken together, this research draws upon new theoretical perspectives that are largely new to the field of information systems (IS), but that offer rich opportunities for theory building and empirical research in settings that will be of high interdisciplinary interest. I believe that such interdisciplinary studies have the potential to provide a distinctive foundation for IS research and can also serve as a guide to research on other economic phenomena in e-commerce

Design of Microelectrode Arrays for The Dnaorigami Orientation Control and the Long-Term Stable Measurement of Bacteria

Microelectrode arrays (MEAs) have great potential in a variety of emerging applications, including brain-machine interfaces (BMIs), point-of-care (PoC) devices, in vitro drug screening, molecular sensing, and bio-microelectromechanical systems (bioMEMs). Also, electrical signals can be delivered through MEAs to stimulate cells and manipulate molecules. DNA origami is one of the promising technology for nanoelectronics and nano-optical devices. The performance of nano-optical devices depends on the precise position and orientation of optical components. To resolve this challenge, the method to control DNA origami orientation through Dielectrophoresis (DEP) will be discussed. Achieving high-resolution analysis with electrochemical sensing modalities necessitates the use of microelectrode arrays (MEAs). Ag/AgCl quasi-reference electrodes integrated with MEAs have been shown in many studies. To fabricate on-chip Ag/AgCl quasi reference electrodes, electrochemically deposition and printing have been utilized. However, these methods are not scalable and require unnecessary circuitry for complementary metal-oxide-semiconductor (CMOS) chips, respectively. Moreover, for long-term measurement of living cells, the biocompatible coating is needed for Ag/AgCl quasi-reference electrode. Here, highly miniaturized, scalable Ag/AgCl quasi-reference electrodes with long-term stable open-circuit voltage (OCV) and biocompatibility will be provided.M.S

Stateless Puzzles for Real Time Online Fraud Preemption

The profitability of fraud in online systems such as app markets and social networks marks the failure of existing defense mechanisms. In this paper, we propose FraudSys, a real-time fraud preemption approach that imposes Bitcoin-inspired computational puzzles on the devices that post online system activities, such as reviews and likes. We introduce and leverage several novel concepts that include (i) stateless, verifiable computational puzzles, that impose minimal performance overhead, but enable the efficient verification of their authenticity, (ii) a real-time, graph-based solution to assign fraud scores to user activities, and (iii) mechanisms to dynamically adjust puzzle difficulty levels based on fraud scores and the computational capabilities of devices. FraudSys does not alter the experience of users in online systems, but delays fraudulent actions and consumes significant computational resources of the fraudsters. Using real datasets from Google Play and Facebook, we demonstrate the feasibility of FraudSys by showing that the devices of honest users are minimally impacted, while fraudster controlled devices receive daily computational penalties of up to 3,079 hours. In addition, we show that with FraudSys, fraud does not pay off, as a user equipped with mining hardware (e.g., AntMiner S7) will earn less than half through fraud than from honest Bitcoin mining

The Impact of Network Neutrality Violation on the Streaming Platform Ecosystem : Evidence from Twitch TV

The widespread use of media streaming services has resulted in a surge in network traffic, triggering debates on network usage fees between Internet service providers (ISPs) and content providers (CPs). As a response to network usage fees imposed by ISPs, CPs have opted to provide discriminatory service quality as a means of mitigating costs associated with high traffic volume. In 2022, a leading Korean ISP charged discriminatory network usage fees to Twitch TV, the media streaming platform, due to its excessive network traffic. In response, Twitch implemented a discriminatory service quality reduction policy. Our study examines the impact of this policy on the streaming platform ecosystem. Our results indicate that the implementation of the service quality reduction led to a remarkable decline in the number of viewers, which then resulted in adverse effects for streamers. This study contributes to the literature on network neutrality violation by offering empirical evidence

Assessing A New IT Service Model, Cloud Computing

Recently we have witnessed a new kind of IT advancement. It is a phenomenon where various types of IT capabilities are centralized into data centers to ensure that such resources are available wherever and whenever they are needed. Cloud computing is the latest version of IT service practice that reflects such new trends in IT. Although cloud computing is considered a paradigm shift of IT service design and delivery in IS communities and generates large amounts of interest from business entities, few studies have examined this new IT and business environment. To better understand the organizational application of cloud computing, this study aims both to investigate economic payoffs from cloud computing investment and explore cloud computing adoption within the firm. This study is one of the first of its kinds to assess this new IT service model (i.e., cloud computing) using empirical validation. The proposed study can make contributions to the IS literature by (1) extending the boundary of the IS literature by reflecting the new trend of the IT industry; (2) continuing the debate about business value of IT; and (3) establishing a theoretical framework for cloud computing adoption, which can be applied to further studies on cloud computing