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4th International Workshop on Human Brain and Artificial Intelligence, HBAI 2024

作者： Pan, Guandong Wu, Zhaobang Yang, Yaqian Wang, Xin Liu, Longzhao Zheng, Zhiming Tang, Shaoting School of Computer Science and Engineering Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Key Laboratory of Mathematics Informatics and Behavioral Semantics Beihang University Beijing100191 China Institute of Medical Artificial Intelligence Binzhou Medical University Yantai264003 China Zhongguancun Laboratory Beijing100094 China Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beihang University Beijing100191 China PengCheng Laboratory Shenzhen518055 China State Key Lab of Software Development Environment Beihang University Beijing100191 China

ISBN: (纸本)9789819640003

The need for automatic and high-quality emotion annotation is paramount in applications such as continuous emotion recognition and video highlight detection, yet achieving this through manual human annotations is challenging. Inspired by inter-subject correlation (ISC) utilized in neuroscience, this study introduces a novel Electroencephalography (EEG) based ISC methodology that leverages a single-electrode and feature-based dynamic approach. Our contributions are three folds: Firstly, we reidentify two potent emotion features suitable for classifying emotions-first-order difference (FD) an differential entropy (DE). Secondly, through the use of overall correlation analysis, we demonstrate the heterogeneous synchronized performance of electrodes. This performance aligns with neural emotion patterns established in prior studies, thus validating the effectiveness of our approach. Thirdly, by employing a sliding window correlation technique, we showcase the significant consistency of dynamic ISCs across various features or key electrodes in each analyzed film clip. Our findings indicate the method’s reliability in capturing consistent, dynamic shared neural synchrony among individuals, triggered by evocative film stimuli. This underscores the potential of our approach to serve as an indicator of continuous human emotion arousal. The implications of this research are significant for advancements in affective computing and the broader neuroscience field, suggesting a streamlined and effective tool for emotion analysis in real-world applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electroencephalography (EEG) Emotion Annotation Inter-subject Correlation

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On the complexity of package recommendation problems 12

On the complexity of package recommendation problems

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31st ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, PODS '12

作者： Deng, Ting Fan, Wenfei Geerts, Floris School of Computer Science and Engineering Beihang University Beijing China Lab. for Foundations of Computer Science School of Informatics University of Edinburgh Edinburgh United Kingdom Dept. of Mathematics and Computer Science University of Antwerp Antwerp Belgium

ISBN: (纸本)9781450312486

Recommendation systems aim to recommend items that are likely to be of interest to users. This paper investigates several issues fundamental to such systems. (1) We model recommendation systems for packages of items. We use queries to specify multi-criteria for item selections and express compatibility constraints on items in a package, and use functions to compute the cost and usefulness of items to a user. (2) We study recommendations of points of interest, to suggest top-k packages. We also investigate recommendations of top-k items, as a special case. In addition, when sensible suggestions cannot be found, we propose query relaxation recommendations to help users revise their selection criteria, or adjustment recommendations to guide vendors to modify their item collections. (3) We identify several problems, to decide whether a set of packages makes a top-k recommendation, whether a rating bound is maximum for selecting top-k packages, whether we can relax the selection query to find packages that users want, and whether we can update a bounded number of items such that the users' requirements can be satisfied. We also study function problems for computing top-k packages, and counting problems to find how many packages meet the user's criteria. (4) We establish the upper and lower bounds of these problems, all matching, for combined and data complexity. These results reveal the impact of variable sizes of packages, the presence of compatibility constraints, as well as a variety of query languages for specifying selection criteria and compatibility constraints, on the analyses of these problems. © 2012 ACM.

关键词： Recommender systems

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Potential Indicator for Continuous Emotion Arousal by Dynamic Neural Synchrony

arXiv

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arXiv 2025年

作者： Pan, Guandong Wu, Zhaobang Yang, Yaqian Wang, Xin Liu, Longzhao Zheng, Zhiming Tang, Shaoting School of Computer Science and Engineering Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Key laboratory of Mathematics Informatics and Behavioral Semantics Beihang University Beijing100191 China Institute of Medical Artificial Intelligence Binzhou Medical University Yantai264003 China Zhongguancun Laboratory Beijing100094 China Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beihang University Beijing100191 China PengCheng Laboratory Shenzhen518055 China State Key Lab of Software Development Environment Beihang University Beijing100191 China

The need for automatic and high-quality emotion annotation is paramount in applications such as continuous emotion recognition and video highlight detection, yet achieving this through manual human annotations is challenging. Inspired by inter-subject correlation (ISC) utilized in neuroscience, this study introduces a novel Electroencephalography (EEG) based ISC methodology that leverages a single-electrode and feature-based dynamic approach. Our contributions are three folds: Firstly, we reidentify two potent emotion features suitable for classifying emotions—first-order difference (FD) an differential entropy (DE). Secondly, through the use of overall correlation analysis, we demonstrate the heterogeneous synchronized performance of electrodes. This performance aligns with neural emotion patterns established in prior studies, thus validating the effectiveness of our approach. Thirdly, by employing a sliding window correlation technique, we showcase the significant consistency of dynamic ISCs across various features or key electrodes in each analyzed film clip. Our findings indicate the method’s reliability in capturing consistent, dynamic shared neural synchrony among individuals, triggered by evocative film stimuli. This underscores the potential of our approach to serve as an indicator of continuous human emotion arousal. The implications of this research are significant for advancements in affective computing and the broader neuroscience field, suggesting a streamlined and effective tool for emotion analysis in real-world applications. © 2025, CC BY-NC-SA.

关键词： Neurons

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AI in the 21st century - With historical reflections

AI in the 21st century - With historical reflections

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作者： Lungarella, Max Iida, Fumiya Bongard, Josh C. Pfeifer, Rolf Dept. of Informatics University of Zurich Switzerland Computer Science and Artificial Intelligence Lab. MIT United States Dept. of Computer Science University of Vermont United States

ISBN: (纸本)9783540772958

The discipline of Artificial Intelligence (AI) was born in the summer of 1956 at Dartmouth College in Hanover, New Hampshire. Half of a century has passed, and AI has turned into an important field whose influence on our daily lives can hardly be overestimated. The original view of intelligence as a computer program - a set of algorithms to process symbols - has led to many useful applications now found in internet search engines, voice recognition software, cars, home appliances, and consumer electronics, but it has not yet contributed significantly to our understanding of natural forms of intelligence. Since the 1980s, AI has expanded into a broader study of the interaction between the body, brain, and environment, and how intelligence emerges from such interaction. This advent of embodiment has provided an entirely new way of thinking that goes well beyond artificial intelligence proper, to include the study of intelligent action in agents other than organisms or robots. For example, it supplies powerful metaphors for viewing corporations, groups of agents, and networked embedded devices as intelligent and adaptive systems acting in highly uncertain and unpredictable environments. In addition to giving us a novel outlook on information technology in general, this broader view of AI also offers unexpected perspectives into how to think about ourselves and the world around us. In this chapter, we briefly review the turbulent history of AI research, point to some of its current trends, and to challenges that the AI of the 21st century will have to face. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Artificial intelligence

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Depression and self-harm risk assessment in online forums

Depression and self-harm risk assessment in online forums

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2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017

作者： Yates, Andrew Cohan, Arman Goharian, Nazli Max Planck Institute for Informatics Saarland Informatics Campus Saarbruecken Germany Information Retrieval Lab Department of Computer Science Georgetown University WashingtonDC United States

ISBN: (纸本)9781945626838

Users suffering from mental health conditions often turn to online resources for support, including specialized online support communities or general communities such as Twitter and Reddit. In this work, we present a framework for supporting and studying users in both types of communities. We propose methods for identifying posts in support communities that may indicate a risk of self-harm, and demonstrate that our approach outperforms strong previously proposed methods for identifying such posts. Self-harm is closely related to depression, which makes identifying depressed users on general forums a crucial related task. We introduce a large-scale general forum dataset consisting of users with self-reported depression diagnoses matched with control users. We show how our method can be applied to effectively identify depressed users from their use of language alone. We demonstrate that our method outperforms strong baselines on this general forum dataset. © 2017 Association for Computational Linguistics.

关键词： Risk assessment

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An ontology-driven personalization framework for designing theory-driven self-management interventions

An ontology-driven personalization framework for designing t...

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AIME 2013 Joint Workshop on Knowledge Representation for Healthcare and Process-Oriented Information Systems in Healthcare, KR4HC 2013/ProHealth 2013

作者： Abidi, Syed Sibte Raza Abidi, Samina NICHE Research Lab Faculty of Computer Science Dalhousie University Canada Medical Informatics Faculty of Medicine Dalhousie University Canada

ISBN: (纸本)9783319039152

We present a patient-centered self-management framework that aims to assist individuals to achieve self-efficacy in terms of self-management of their chronic condition. We have incorporated an evidence-driven behavior model-i.e. the Social Cognition Theory (SCT)-to personalize the selfmanagement educational content based on the individual's health and psychosocial profile. We have taken a knowledge management approach to the development of the self-management framework where we have modeled the SCT, educational content and strategies, assessment tools and the personalization logic using an OWL-DL based ontology. The execution of the knowledge encapsulated within the SCT ontology allows for the dynamic generation of a patient's profile and the selection of the relevant self-management strategies, educational and motivational messages. We applied our self-management framework to develop a self-management program for cardiac conditions. © Springer International Publishing Switzerland 2013.

关键词： Ontology

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Learning neighborhoods for metric learning

Learning neighborhoods for metric learning

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2012 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2012

作者： Wang, Jun Woznica, Adam Kalousis, Alexandros AI Lab. Department of Computer Science University of Geneva Switzerland Department of Business Informatics University of Applied Sciences Switzerland

ISBN: (纸本)9783642334597

Metric learning methods have been shown to perform well on different learning tasks. Many of them rely on target neighborhood relationships that are computed in the original feature space and remain fixed throughout learning. As a result, the learned metric reflects the original neighborhood relations. We propose a novel formulation of the metric learning problem in which, in addition to the metric, the target neighborhood relations are also learned in a two-step iterative approach. The new formulation can be seen as a generalization of many existing metric learning methods. The formulation includes a target neighbor assignment rule that assigns different numbers of neighbors to instances according to their quality;'high quality' instances get more neighbors. We experiment with two of its instantiations that correspond to the metric learning algorithms LMNN and MCML and compare it to other metric learning methods on a number of datasets. The experimental results show state-of-the-art performance and provide evidence that learning the neighborhood relations does improve predictive performance. © 2012 Springer-Verlag.

关键词： Learning algorithms

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Knowledge Mapping System Implementation in Knowledge Management: A Systematic Literature Review 3

Knowledge Mapping System Implementation in Knowledge Managem...

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3rd International Conference on Information Management and Technology, ICIMTech 2018

作者： Hakim, Shidiq Al Sensuse, Dana Indra Faculty of Computer Science University of Indonesia Depok Research Center for Informatics Cibinong Indonesia Faculty of Computer Science University of Indonesia E-Government and E-Business Research Lab Depok Indonesia

ISBN: (纸本)9781538658215

Knowledge mapping has been studied widely in knowledge management context, but the terminology ofknowledge map system (KMSs) is not been much studied and it needs to identify state the art KMSs topic from a literature review to propose the future research. The method refers to the systematic literature reviewas guidelines from Kitchenham, this research gathers, synthesizes, and analyses some paper based on keyword 'knowledge map system' or 'knowledge mapping system' and 'knowledge management', where it published from 2008 until 2017 on four international electronic databases and using predefined review protocol. We obtained 9 articles used in this study and find that most design systems use customized with some computational *** scope is still a lot of focus on enterprise and virtual community, accordingly it needs to be developed further system for the country aspublic services and also validation method that combines elements of content and software. © 2018 IEEE.

关键词： Knowledge management

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University of lugano at TREC 2010

University of lugano at TREC 2010

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19th Text REtrieval Conference, TREC 2010

作者： Keikha, Mostafa Mahdabi, Parvaz Gerani, Shima Inches, Giacomo Parapary, Javier Carman, Mark Crestani, Fabio Department of Informatics University of Lugano Lugano Switzerland Dept. of Computer Science Information Retrieval Lab University of A Coruna Spain

We report on the University of Lugano's participation in the Blog and Session tracks of TREC 2010. In particular we describe our system for performing blog distillation, faceted search, top stories identification ... 详细信息

关键词： Distillation

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Ambient wood: Designing new forms of digital augmentation for learning outdoors 04

Ambient wood: Designing new forms of digital augmentation fo...

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3rd International Conference on Interaction Design and Children, IDC 2004

作者： Rogers, Y. Price, S. Fitzpatrick, G. Fleck, R. Harris, E. Smith, H. Randell, C. Muller, H. O'malley, C. Stanton, D. Thompson, M. Weal, M. School of Informatics Indiana University United States Interact Lab Dept of Informatics University of Sussex United Kingdom Computer Science Dept. Bristol University United Kingdom Mixed Reality Lab Nottingham University United Kingdom Dept of Electronics and Computer Science University of Southampton United Kingdom

ISBN: (纸本)1581137915

Ubiquitous and mobile technologies provide opportunities for designing novel learning experiences that move out of the classroom. Information can be presented and interacted with in a variety of ways while exploring a physical environment. A key issue this raises is when, where, what and how much? Our research is concerned with the design, delivery and interaction of digital information when learning about ecology outdoors. We present a framework of the different forms of digital augmentation and the different processes by which they can be accessed. Using the framework, we designed an outdoors learning experience, aimed at encouraging students to carry out contextualized scientific enquiry and to reflect on their interactions. Pairs of 11-12 year olds explored a woodland and were presented at certain times with different forms of digital augmentation. Our study showed that this kind of exploration promoted interpretation and reflection at a number of levels of abstraction. © 2004 ACM.

关键词： Ubiquitous computing

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