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- Adversarial training (1)
- Analyst forecast (1)
- Cloud computing (1)
- Domain relationships learning (1)
- Double-learning (1)
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- E-commerce User Alignment (1)
- Evaluation methods (1)
- Firm capabilities (1)
- Heterogeneous Embedding Propagation (1)
- Heterogeneous Interaction Graph (1)
- IT services (1)
- IT strategy (1)
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- Learning (1)
- Location-based services (1)
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- Online product reviews (1)
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- Operand and operant resources (1)
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- Predictive modeling (1)
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- Recommender Systems (1)
- Resource-based view (1)
- Retrieval-based question answering (1)
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- Strategic value appropriation path (1)
- Synchronization (1)
- Technology implementation (1)
- Transfer learning (1)
Articles 1 - 8 of 8
Full-Text Articles in Physical Sciences and Mathematics
Double Learning Or Double Blinding: An Investigation Of Vendor Private Information Acquisition And Consumer Learning Via Online Reviews, Nan Hu, Kevin E. Dow, Alain Yee Loong Chong, Ling Liu
Double Learning Or Double Blinding: An Investigation Of Vendor Private Information Acquisition And Consumer Learning Via Online Reviews, Nan Hu, Kevin E. Dow, Alain Yee Loong Chong, Ling Liu
Research Collection School Of Computing and Information Systems
In this paper, building upon information acquisition theory and using portfolio methods and system equations, we made an empirical investigation into how online vendors and consumers are learning from each other, and how online reviews, prices, and sales interact among each other. First, this study shows that vendors acquire information from both private and public channels to learn the quality of their products to make price adjustment. Second, for the more popular products and newly released products, vendors are more motivated to acquire private information that is more precise than the average precision to adjust their price. Third, we document …
Heterogeneous Embedding Propagation For Large-Scale E-Commerce User Alignment, Vincent W. Zheng, Mo Sha, Yuchen Li, Hongxia Yang, Yuan Fang, Zhenjie Zhang, Kian-Lee Tan, Kevin Chen-Chuan Chang
Heterogeneous Embedding Propagation For Large-Scale E-Commerce User Alignment, Vincent W. Zheng, Mo Sha, Yuchen Li, Hongxia Yang, Yuan Fang, Zhenjie Zhang, Kian-Lee Tan, Kevin Chen-Chuan Chang
Research Collection School Of Computing and Information Systems
We study the important problem of user alignment in e-commerce: to predict whether two online user identities that access an e-commerce site from different devices belong to one real-world person. As input, we have a set of user activity logs from Taobao and some labeled user identity linkages. User activity logs can be modeled using a heterogeneous interaction graph (HIG), and subsequently the user alignment task can be formulated as a semi-supervised HIG embedding problem. HIG embedding is challenging for two reasons: its heterogeneous nature and the presence of edge features. To address the challenges, we propose a novel Heterogeneous …
A Strategic Value Appropriation Path For Cloud Computing, Abhishek Kathuria, Arti Mann, Jiban Khuntia, Robert J. Kauffman
A Strategic Value Appropriation Path For Cloud Computing, Abhishek Kathuria, Arti Mann, Jiban Khuntia, Robert J. Kauffman
Research Collection School Of Computing and Information Systems
Cloud-based information management is one of the leading competitive differentiation strategies for firms. With the increasing criticality of information management in value creation and process support, establishing an integrated capability with cloud computing is vital for organizational success in the changing landscape of business competition. These issues have received scant attention, however. We draw on the resource-based view, dynamic capability hierarchy concepts, and the perspective of operand and operant resources to suggest a cloud value appropriation model for firms. We argue that, to appropriate business value from cloud computing, the firm needs to effectively deploy cloud computing and leverage cloud …
Modeling Contemporaneous Basket Sequences With Twin Networks For Next-Item Recommendation, Duc Trong Le, Hady W. Lauw, Yuan Fang
Modeling Contemporaneous Basket Sequences With Twin Networks For Next-Item Recommendation, Duc Trong Le, Hady W. Lauw, Yuan Fang
Research Collection School Of Computing and Information Systems
Our interactions with an application frequently leave a heterogeneous and contemporaneous trail of actions and adoptions (e.g., clicks, bookmarks, purchases). Given a sequence of a particular type (e.g., purchases)-- referred to as the target sequence, we seek to predict the next item expected to appear beyond this sequence. This task is known as next-item recommendation. We hypothesize two means for improvement. First, within each time step, a user may interact with multiple items (a basket), with potential latent associations among them. Second, predicting the next item in the target sequence may be helped by also learning from another supporting sequence …
A Proposal For A Decentralized Liquidity Savings Mechanism With Side Payments, Adam Fugal, Rodney Garratt, Zhiling Guo, Dave Hudson
A Proposal For A Decentralized Liquidity Savings Mechanism With Side Payments, Adam Fugal, Rodney Garratt, Zhiling Guo, Dave Hudson
Research Collection School Of Computing and Information Systems
In most countries, the central bank provides the medium to physically settle the smallest payments (cash) and the means to electronically settle the largest payments, which typically are wholesale payments between banks. For the latter purpose the central bank usually operates a system through which banks can settle payments in central bank money. Historically, interbank payments were settled via (end of day) netting systems, but as volumes and values increased central banks became worried about the risks inherent in deferred net settlement systems, so most central banks opted for the implementation of a Real Time Gross Settlement (RTGS) system. With …
Towards Easy Comparison Of Local Businesses Using Online Reviews, Yong Wang, Hammad Haleem, Conglei Shi, Yanhong Wu, Xun Zhao, Siwei Fu, Huamin Qu
Towards Easy Comparison Of Local Businesses Using Online Reviews, Yong Wang, Hammad Haleem, Conglei Shi, Yanhong Wu, Xun Zhao, Siwei Fu, Huamin Qu
Research Collection School Of Computing and Information Systems
With the rapid development of e-commerce, there is an increasing number of online review websites, such as Yelp, to help customers make better purchase decisions. Viewing online reviews, including the rating score and text comments by other customers, and conducting a comparison between different businesses are the key to making an optimal decision. However, due to the massive amount of online reviews, the potential difference of user rating standards, and the significant variance of review time, length, details and quality, it is difficult for customers to achieve a quick and comprehensive comparison. In this paper, we present E-Comp, a carefully-designed …
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 …
Modelling Domain Relationships For Transfer Learning On Retrieval-Based Question Answering Systems In E-Commerce, Jianfei Yu, Minghui Qiu, Jing Jiang, Jun Huang, Shuangyong Song, Wei Chu, Haiqing Chen
Modelling Domain Relationships For Transfer Learning On Retrieval-Based Question Answering Systems In E-Commerce, Jianfei Yu, Minghui Qiu, Jing Jiang, Jun Huang, Shuangyong Song, Wei Chu, Haiqing Chen
Research Collection School Of Computing and Information Systems
Nowadays, it is a heated topic for many industries to build automatic question-answering (QA) systems. A key solution to these QA systems is to retrieve from a QA knowledge base the most similar question of a given question, which can be reformulated as a paraphrase identification (PI) or a natural language inference (NLI) problem. However, most existing models for PI and NLI have at least two problems: They rely on a large amount of labeled data, which is not always available in real scenarios, and they may not be efficient for industrial applications. In this paper, we study transfer learning …