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Articles 1 - 8 of 8
Full-Text Articles in Physical Sciences and Mathematics
Explanation Guided Contrastive Learning For Sequential Recommendation, Lei Wang, Ee-Peng Lim, Zhiwei Liu, Tianxiang Zhao
Explanation Guided Contrastive Learning For Sequential Recommendation, Lei Wang, Ee-Peng Lim, Zhiwei Liu, Tianxiang Zhao
Research Collection Lee Kong Chian School Of Business
Recently, contrastive learning has been applied to the sequential recommendation task to address data sparsity caused by users with few item interactions and items with few user adoptions. Nevertheless, the existing contrastive learning-based methods fail to ensure that the positive (or negative) sequence obtained by some random augmentation (or sequence sampling) on a given anchor user sequence remains to be semantically similar (or different). When the positive and negative sequences turn out to be false positive and false negative respectively, it may lead to degraded recommendation performance. In this work, we address the above problem by proposing Explanation Guided Augmentations …
Artificial Intelligence, Consumers, And The Experience Economy, Hannah H. Chang, Anirban Mukherjee
Artificial Intelligence, Consumers, And The Experience Economy, Hannah H. Chang, Anirban Mukherjee
Research Collection Lee Kong Chian School Of Business
The term Artificial Intelligence (AI) was first used by McCarthy, Minsky, Rochester, and Shannon in a proposal for a summer research project in 1955 (Solomonoff, 1985). It is widely and commonly defined to be “the science and engineering of making intelligent machines” (McCarthy, 2006). Recent technological advances and methodological developments have made AI pervasive in new marketing offerings, ranging from self-driving cars, intelligent voice assistants such as Amazon’s Alexa, to burger-making robots at restaurants and rack-moving robots inside warehouses such as Amazon’s family of robots (Kiva, Pegasus, Xanthus) and delivery drones. There is optimism, and perhaps even over-optimism, of the …
Using Machine Learning To Extract Insights From Consumer Data, Hannah H. Chang, Anirban Mukherjee
Using Machine Learning To Extract Insights From Consumer Data, Hannah H. Chang, Anirban Mukherjee
Research Collection Lee Kong Chian School Of Business
Advances in digital technology have led to the digitization of everyday activities of billions of people around the world, generating vast amounts of data on human behavior. From what people buy, to what information they search for, to how they navigate the social, digital, and physical world, human behavior can now be measured at a scale and level of precision that human history has not witnessed before. These developments have created unprecedented opportunities for those interested in understanding observable human behavior–social scientists, businesses, and policymakers—to (re)examine theoretical and substantive questions regarding people’s behavior. Moreover, technology has led to the emergence …
Distinctive Features Of Nonverbal Behavior And Mimicry In Application Interviews Through Data Analysis And Machine Learning, Sanne Rogiers, Elias Corneillie, Filip Lievens, Frederik Anseel, Peter Veelaert, Wilfried Philips
Distinctive Features Of Nonverbal Behavior And Mimicry In Application Interviews Through Data Analysis And Machine Learning, Sanne Rogiers, Elias Corneillie, Filip Lievens, Frederik Anseel, Peter Veelaert, Wilfried Philips
Research Collection Lee Kong Chian School Of Business
This paper reveals the characteristics and effects of nonverbal behavior and human mimicry in the context of application interviews. It discloses a novel analyzation method for psychological research by utilizing machine learning. In comparison to traditional manual data analysis, machine learning proves to be able to analyze the data more deeply and to discover connections in the data invisible to the human eye. The paper describes an experiment to measure and analyze the reactions of evaluators to job applicants who adopt specific behaviors: mimicry, suppress, immediacy and natural behavior. First, evaluation of the applicant qualifications by the interviewer reveals …
Hci Education And Ux Practice: Highlights From Singapore, Tamas Makany, Dharani Perera-Schulz
Hci Education And Ux Practice: Highlights From Singapore, Tamas Makany, Dharani Perera-Schulz
Research Collection Lee Kong Chian School Of Business
This position paper highlights trends in education, practice, and support of HCI/UX in Singapore, a small city-state island in Southeast Asia. The paper was prepared for the 2022 Southeast Asia Computer-Human Interaction (SEACHI'22) virtual workshop on Apr 14, 2022, as part of the ACM CHI Conference on Human Factors in Computing Systems (CHI'22) international conference.
Hci In Southeast Asia: The Journey Forward, E. Sari, J.A. Tedjasaputra, Y. Kurniawan, E. Zulaikha, A. Asfarian, M. Ghazali, A. Sivaji, J.A. Abu Bakar, C.Y. Wong, N.M. Norowi, Tamas Makany, D. Perera-Schulz, T. Chintakovid, S. Nuchitprasitchai, Ethel Ong
Hci In Southeast Asia: The Journey Forward, E. Sari, J.A. Tedjasaputra, Y. Kurniawan, E. Zulaikha, A. Asfarian, M. Ghazali, A. Sivaji, J.A. Abu Bakar, C.Y. Wong, N.M. Norowi, Tamas Makany, D. Perera-Schulz, T. Chintakovid, S. Nuchitprasitchai, Ethel Ong
Research Collection Lee Kong Chian School Of Business
SEACHI 2022 has been conducted to bring HCI and UX leaders in Southeast Asia to discuss the current state-of-the-art HCI and UX teaching, practice, and support they experience in their region. This activity aims to explore the potentials and challenges and identify the gaps amongst different sectors in different countries. Through this workshop, we will have a common understanding of what we face. It explores how we can work collaboratively to achieve a better purpose, i.e., to grow HCI and UX fields in Southeast Asia. This one-day online workshop was conducted as a collocated event of CHI 2022 and was …
To Buy Green Or Not To Buy Green: Do Structural Dependencies Block Ecological Responsiveness?, Simon J.D. Schillebeeckx, Teemu Kautonen, Henri Hakata
To Buy Green Or Not To Buy Green: Do Structural Dependencies Block Ecological Responsiveness?, Simon J.D. Schillebeeckx, Teemu Kautonen, Henri Hakata
Research Collection Lee Kong Chian School Of Business
Despite the significant increase in interest in sustainable business practices, decisions on switching to more environmentally friendly input materials are understudied. In a conjoint experiment, we presented 267 Finnish manufacturing firms with an opportunity to acquire an alternative, more ecological input material and investigated their willingness to switch to that material. We find that in general, firms are willing to substitute their current principal input with a more ecological alternative under conditions of functional parity. However, such willingness is contingent on the firm’s value creation structures. Specifically, if the products and processes driving the firm’s value creation rely more on …
Outsourcing Climate Change, Rui Dai, Rui Duan, Hao Liang, Lilian Ng
Outsourcing Climate Change, Rui Dai, Rui Duan, Hao Liang, Lilian Ng
Research Collection Lee Kong Chian School Of Business
This paper examines whether and how firms combat climate change. Our study provides robust evidence that firms outsource part of their carbon emissions to foreign suppliers and shows how internal and external stakeholders significantly shape firms' environmental policies. Furthermore, firms tend to seek a foreign supplier and decrease their emission abatement efforts as pressure to reduce domestic emissions intensifies. These firms are also less incentivized to develop green technologies. Finally, we find that outsourcing emissions has real and economic consequences, with investors demanding a higher carbon premium for their exposures to carbon risks associated with increased outsourced emissions.