Pub Date : 2024-02-28DOI: 10.1109/mis.2024.3359896
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Pub Date : 2024-02-28DOI: 10.1109/mis.2023.3344353
Amit Sheth, Kaushik Roy
The rapid progression of artificial intelligence (AI) systems, facilitated by the advent of large language models (LLMs), has resulted in their widespread application to provide human assistance across diverse industries. This trend has sparked significant discourse centered around the ever-increasing need for LLM-based AI systems to function among humans as a part of human society. Toward this end, neurosymbolic AI systems are attractive because of their potential to enable and interpretable interfaces for facilitating value-based decision making by leveraging explicit representations of shared values. In this article, we introduce substantial extensions to Kahneman’s System 1 and System 2 framework and propose a neurosymbolic computational framework called value-inspired AI (VAI). It outlines the crucial components essential for the robust and practical implementation of VAI systems, representing and integrating various dimensions of human values. Finally, we further offer insights into the current progress made in this direction and outline potential future directions for the field.
随着大型语言模型（LLM）的出现，人工智能（AI）系统得到了快速发展，并被广泛应用于各行各业，为人类提供帮助。这一趋势引发了围绕基于 LLM 的人工智能系统作为人类社会的一部分在人类中发挥作用的日益增长的需求的重要讨论。为此，神经符号人工智能系统颇具吸引力，因为它们有可能利用共同价值观的明确表征，为促进基于价值的决策提供可解释的界面。在本文中，我们介绍了对卡尼曼的系统 1 和系统 2 框架的实质性扩展，并提出了一种称为价值启发式人工智能（VAI）的神经符号计算框架。它概述了 VAI 系统稳健实用的重要组成部分，代表并整合了人类价值观的各个层面。最后，我们进一步深入分析了该领域目前取得的进展，并概述了该领域未来的潜在发展方向。
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Pub Date : 2024-02-28DOI: 10.1109/mis.2023.3343489
Tianxing Wang, Can Wang
A point-of-interest (POI) recommendation becomes the core function of location-based services. Unlike a traditional item recommendation, a POI recommendation has distinct features, such as geographical influences, complex mobility patterns, and a balance between local and global user preferences. Past POI recommendation system research has focused mainly on integrating deep learning models like convolutional neural networks, recurrent neural networks, and attention-based architectures, demonstrating their effectiveness in addressing the dynamic nature of spatial–temporal data in POI recommendation areas. In recent years, with the rise of large language models (LLMs), POI recommendation has produced a number of promising directions. This article first discusses the characteristics and state-of-the-art solutions of POI recommendation, then it introduces potential research directions by integrating the latest LLMs.
兴趣点（POI）推荐成为基于位置服务的核心功能。与传统的物品推荐不同，兴趣点推荐具有明显的特征，如地理影响、复杂的移动模式、本地用户偏好与全球用户偏好之间的平衡等。以往的 POI 推荐系统研究主要集中在卷积神经网络、递归神经网络和基于注意力的架构等深度学习模型的集成上，证明了它们在解决 POI 推荐领域时空数据的动态特性方面的有效性。近年来，随着大型语言模型（LLMs）的兴起，POI 推荐领域出现了许多前景广阔的方向。本文首先讨论了 POI 推荐的特点和最先进的解决方案，然后结合最新的 LLMs 介绍了潜在的研究方向。
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Pub Date : 2024-02-09DOI: 10.1109/mis.2024.3363895
Yanbing Wang, Hong He
{"title":"EEG Emotion Recognition Based on Manifold Geomorphological Features in Riemannian Space","authors":"Yanbing Wang, Hong He","doi":"10.1109/mis.2024.3363895","DOIUrl":"https://doi.org/10.1109/mis.2024.3363895","url":null,"abstract":"","PeriodicalId":13160,"journal":{"name":"IEEE Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":6.4,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139948816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-11DOI: 10.1109/mis.2024.3352977
T. Turchi, A. Malizia, S. Borsci
{"title":"Reflecting on Algorithmic Bias with Design Fiction: the MiniCoDe Workshops","authors":"T. Turchi, A. Malizia, S. Borsci","doi":"10.1109/mis.2024.3352977","DOIUrl":"https://doi.org/10.1109/mis.2024.3352977","url":null,"abstract":"","PeriodicalId":13160,"journal":{"name":"IEEE Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":6.4,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139948821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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