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272 results on '"Schorlemmer, Marco"'

1. Can Interpretability Layouts Influence Human Perception of Offensive Sentences?

Author

Santos, Thiago Freitas dos, Osman, Nardine, and Schorlemmer, Marco

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

This paper conducts a user study to assess whether three machine learning (ML) interpretability layouts can influence participants' views when evaluating sentences containing hate speech, focusing on the "Misogyny" and "Racism" classes. Given the existence of divergent conclusions in the literature, we provide empirical evidence on using ML interpretability in online communities through statistical and qualitative analyses of questionnaire responses. The Generalized Additive Model estimates participants' ratings, incorporating within-subject and between-subject designs. While our statistical analysis indicates that none of the interpretability layouts significantly influences participants' views, our qualitative analysis demonstrates the advantages of ML interpretability: 1) triggering participants to provide corrective feedback in case of discrepancies between their views and the model, and 2) providing insights to evaluate a model's behavior beyond traditional performance metrics.

Published
2024

2. uHelp: intelligent volunteer search for mutual help communities

Author

Osman, Nardine, Rosell, Bruno, Sierra, Carles, Schorlemmer, Marco, Sabater-Mir, Jordi, and Lemus, Lissette

Subjects
Computer Science - Social and Information Networks, Computer Science - Artificial Intelligence
Abstract

When people need help with their day-to-day activities, they turn to family, friends or neighbours. But despite an increasingly networked world, technology falls short in finding suitable volunteers. In this paper, we propose uHelp, a platform for building a community of helpful people and supporting community members find the appropriate help within their social network. Lately, applications that focus on finding volunteers have started to appear, such as Helpin or Facebook's Community Help. However, what distinguishes uHelp from existing applications is its trust-based intelligent search for volunteers. Although trust is crucial to these innovative social applications, none of them have seriously achieved yet a trust-building solution such as that of uHelp. uHelp's intelligent search for volunteers is based on a number of AI technologies: (1) a novel trust-based flooding algorithm that navigates one's social network looking for appropriate trustworthy volunteers; (2) a novel trust model that maintains the trustworthiness of peers by learning from their similar past experiences; and (3) a semantic similarity model that assesses the similarity of experiences. This article presents the uHelp application, describes the underlying AI technologies that allow uHelp find trustworthy volunteers efficiently, and illustrates the implementation details. uHelp's initial prototype has been tested with a community of single parents in Barcelona, and the app is available online at both Apple Store and Google Play.

Published
2023

3. Generating Qualitative Descriptions of Diagrams with a Transformer-Based Language Model

Author

Schorlemmer, Marco, Ballout, Mohamad, Kühnberger, Kai-Uwe, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Lemanski, Jens, editor, Johansen, Mikkel Willum, editor, Manalo, Emmanuel, editor, Viana, Petrucio, editor, Bhattacharjee, Reetu, editor, and Burns, Richard, editor

Published
2024
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4. The uHelp Application

Author

Osman, Nardine, Rosell, Bruno, Koster, Andrew, Schorlemmer, Marco, Sierra, Carles, Sabater-Mir, Jordi, O'Sullivan, Barry, Series Editor, Wooldridge, Michael, Series Editor, and Osman, Nardine, editor

Published
2024
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5. Can Interpretability Layouts Influence Human Perception of Offensive Sentences?

Author

Freitas dos Santos, Thiago, Osman, Nardine, Schorlemmer, Marco, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Calvaresi, Davide, editor, Najjar, Amro, editor, Omicini, Andrea, editor, Aydogan, Reyhan, editor, Carli, Rachele, editor, Ciatto, Giovanni, editor, Hulstijn, Joris, editor, and Främling, Kary, editor

Published
2024
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8. Learning for Detecting Norm Violation in Online Communities

Author

Santos, Thiago Freitas dos, Osman, Nardine, and Schorlemmer, Marco

Subjects
Computer Science - Social and Information Networks, Computer Science - Machine Learning
Abstract

In this paper, we focus on normative systems for online communities. The paper addresses the issue that arises when different community members interpret these norms in different ways, possibly leading to unexpected behavior in interactions, usually with norm violations that affect the individual and community experiences. To address this issue, we propose a framework capable of detecting norm violations and providing the violator with information about the features of their action that makes this action violate a norm. We build our framework using Machine Learning, with Logistic Model Trees as the classification algorithm. Since norm violations can be highly contextual, we train our model using data from the Wikipedia online community, namely data on Wikipedia edits. Our work is then evaluated with the Wikipedia use case where we focus on the norm that prohibits vandalism in Wikipedia edits., Comment: proceedings for International Workshop on Coordination, Organizations, Institutions, Norms and Ethics for Governance of Multi-Agent Systems (COINE), co-located with AAMAS 2021

Published
2021
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10. Modelling the Sense-Making of Diagrams Using Image Schemas

Author

Bourou, Dimitra Anna, Schorlemmer, Marco, and Plaza, Enric

Subjects
cognitive science
Abstract

We model the sense-making process of diagrams as conceptual blends of the diagrams’ geometric configurations with apt image schemas.We specify image schemas and geometric configurations with typed FOL theories. In addition, for the latter, we utilise some Qualitative Spatial Reasoning formalisms. Using an algebraic specification language, we can compute the conceptual blends of image schemas and geometry as category-theoretic colimits.We show through several examples how this model captures the sort of direct inferences we confer to diagrammatic representations due to our embodied cognition. We argue that this approach to sense-making might be of value for the design and application of diagrammatic and graphical visualisations, as well as for AI in general.

Published
2021

11. Learning for Detecting Norm Violation in Online Communities

Author

Freitas dos Santos, Thiago, Osman, Nardine, Schorlemmer, Marco, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Theodorou, Andreas, editor, Nieves, Juan Carlos, editor, and De Vos, Marina, editor

Published
2022
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12. Euler vs Hasse Diagrams for Reasoning About Sets: A Cognitive Approach

Author

Bourou, Dimitra, Schorlemmer, Marco, Plaza, Enric, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Giardino, Valeria, editor, Linker, Sven, editor, Burns, Richard, editor, Bellucci, Francesco, editor, Boucheix, Jean-Michel, editor, and Viana, Petrucio, editor

Published
2022
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14. Vocabulary Alignment in Openly Specified Interactions

Author

Chocron, Paula and Schorlemmer, Marco

Subjects
Computer Science - Multiagent Systems
Abstract

The problem of achieving common understanding between agents that use different vocabularies has been mainly addressed by designing techniques that explicitly negotiate mappings between their vocabularies, requiring agents to share a meta-language. In this paper we consider the case of agents that use different vocabularies and have no meta-language in common, but share the knowledge of how to perform a task, given by the specification of an interaction protocol. For this situation, we present a framework that lets agents learn a vocabulary alignment from the experience of interacting. Unlike previous work in this direction, we use open protocols that constrain possible actions instead of defining procedures, making our approach more general. We present two techniques that can be used either to learn an alignment from scratch or to repair an existent one, and we evaluate experimentally their performance., Comment: 14 pages, accepted at AAMAS 2017

Published
2017

15. Image Schemas and Conceptual Blending in Diagrammatic Reasoning: The Case of Hasse Diagrams

Author

Bourou, Dimitra, Schorlemmer, Marco, Plaza, Enric, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Basu, Amrita, editor, Stapleton, Gem, editor, Linker, Sven, editor, Legg, Catherine, editor, Manalo, Emmanuel, editor, and Viana, Petrucio, editor

Published
2021
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18. Chapter 1 Amalgams, Colimits, and Conceptual Blending

Author

Bou, Félix, Plaza, Enric, Schorlemmer, Marco, Pachet, François, Series Editor, Gervás, Pablo, Series Editor, Passerini, Andrea, Series Editor, Degli Esposti, Mirko, Series Editor, Confalonieri, Roberto, editor, Pease, Alison, editor, Schorlemmer, Marco, editor, Besold, Tarek R., editor, Kutz, Oliver, editor, Maclean, Ewen, editor, and Kaliakatsos-Papakostas, Maximos, editor

Published
2018
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19. Chapter 2 Computational Aspects of Concept Invention

Author

Confalonieri, Roberto, Plaza, Enric, Schorlemmer, Marco, Pachet, François, Series Editor, Gervás, Pablo, Series Editor, Passerini, Andrea, Series Editor, Degli Esposti, Mirko, Series Editor, Confalonieri, Roberto, editor, Pease, Alison, editor, Schorlemmer, Marco, editor, Besold, Tarek R., editor, Kutz, Oliver, editor, Maclean, Ewen, editor, and Kaliakatsos-Papakostas, Maximos, editor

Published
2018
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24. ASP, Amalgamation, and the Conceptual Blending Workflow

Author

Eppe, Manfred, Maclean, Ewen, Confalonieri, Roberto, Kutz, Oliver, Schorlemmer, Marco, Plaza, Enric, Goebel, Randy, Series editor, Tanaka, Yuzuru, Series editor, Wahlster, Wolfgang, Series editor, Calimeri, Francesco, editor, Ianni, Giovambattista, editor, and Truszczynski, Miroslaw, editor

Published
2015
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31. Trust Alignment: A Sine Qua Non of Open Multi-agent Systems

Author

Koster, Andrew, Sabater-Mir, Jordi, Schorlemmer, Marco, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Meersman, Robert, editor, Dillon, Tharam, editor, Herrero, Pilar, editor, Kumar, Akhil, editor, Reichert, Manfred, editor, Qing, Li, editor, Ooi, Beng-Chin, editor, Damiani, Ernesto, editor, Schmidt, Douglas C., editor, White, Jules, editor, Hauswirth, Manfred, editor, Hitzler, Pascal, editor, and Mohania, Mukesh, editor

Published
2011
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33. Learning for Detecting Norm Violation in Online Communities

Author

Osman, Nardine [0000-0002-2766-3475], Schorlemmer, Marco [0000-0002-9591-3325], Freitas Dos Santos, Thiago [0000-0003-3800-7243], Freitas Dos Santos, Thiago, Osman, Nardine, Schorlemmer, Marco, Osman, Nardine [0000-0002-2766-3475], Schorlemmer, Marco [0000-0002-9591-3325], Freitas Dos Santos, Thiago [0000-0003-3800-7243], Freitas Dos Santos, Thiago, Osman, Nardine, and Schorlemmer, Marco

Abstract

[EN]In this paper, we focus on normative systems for online communities. The paper addresses the issue that arises when different community members interpret these norms in different ways, possibly leading to unexpected behavior in interactions, usually with norm violations that affect the individual and community experiences. To address this issue, we propose a framework capable of detecting norm violations and providing the violator with information about the features of their action that makes this action violate a norm. We build our framework using Machine Learning, with Logistic Model Trees as the classification algorithm. Since norm violations can be highly contextual, we train our model using data from the Wikipedia online community, namely data on Wikipedia edits. Our work is then evaluated with the Wikipedia use case where we focus on the norm that prohibits vandalism in Wikipedia edits.

Published
2021

34. A Uniform Model of Computational Conceptual Blending

Author

Schorlemmer, Marco [0000-0002-9591-3325], Plaza, Enric [], Schorlemmer, Marco, Plaza, Enric, Schorlemmer, Marco [0000-0002-9591-3325], Plaza, Enric [], Schorlemmer, Marco, and Plaza, Enric

Abstract

[EN]We present a mathematical model for the cognitive operation of conceptual blending that aims at being uniform across di↵erent representation formalisms, while capturing the relevant structure of this operation. The model takes its inspiration from amalgams as applied in case-based reasoning, but lifts them into the theory of categories so as to follow Joseph Goguen’s intuition for a mathematically precise characterisation of conceptual blending at a representationindependent level of abstraction. We prove that our amalgam-based categorytheoretical model of conceptual blending is essentially equivalent to the pushout model in the ordered category of partial maps as put forward by Joseph Goguen. But unlike Goguen’s approach, our model is more suitable for a computational realisation of conceptual blending, and we exemplify this by concretising our model to computational conceptual blends for various representation formalisms and application domains.

Published
2021

35. I-SSA: Interaction-Situated Semantic Alignment

Author

Atencia, Manuel, Schorlemmer, Marco, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Meersman, Robert, editor, and Tari, Zahir, editor

Published
2008
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37. Open Knowledge : Coordinating Knowledge Sharing through Peer–to–Peer Interaction

Author

Robertson, Dave, Giunchiglia, Fausto, van Harmelen, Frank, Marchese, Maurizio, Sabou, Marta, Schorlemmer, Marco, Shadbolt, Nigel, Siebes, Ronnie, Sierra, Carles, Walton, Chris, Dasmahapatra, Srinandan, Dupplaw, Dave, Lewis, Paul, Yatskevich, Mikalai, Kotoulas, Spyros, Perreau de Pinninck, Adrian, Loizou, Antonis, Carbonell, Jaime G., editor, Siekmann, J\'org, editor, Dastani, Mehdi, editor, El Fallah Seghrouchni, Amal, editor, Leite, João, editor, and Torroni, Paolo, editor

Published
2008
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38. Distributed Norm Enforcement Via Ostracism

Author

Perreau de Pinninck, Adrian, Sierra, Carles, Schorlemmer, Marco, Carbonell, Jaime G., editor, Siekmann, J\'org, editor, Sichman, Jaime Simão, editor, Padget, Julian, editor, Ossowski, Sascha, editor, and Noriega, Pablo, editor

Published
2008
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40. Using Formal Concept Analysis and Information Flow for Modelling and Sharing Common Semantics: Lessons Learnt and Emergent Issues

Author

Kalfoglou, Yannis, Schorlemmer, Marco, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Dau, Frithjof, editor, Mugnier, Marie-Laure, editor, and Stumme, Gerd, editor

Published
2005
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41. On the Emergent Semantic Web and Overlooked Issues

Author

Kalfoglou, Yannis, Alani, Harith, Schorlemmer, Marco, Walton, Chris, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, McIlraith, Sheila A., editor, Plexousakis, Dimitris, editor, and van Harmelen, Frank, editor

Published
2004
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42. Formal Support for Representing and Automating Semantic Interoperability

Author

Kalfoglou, Yannis, Schorlemmer, Marco, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Bussler, Christoph J., editor, Davies, John, editor, Fensel, Dieter, editor, and Studer, Rudi, editor

Published
2004
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43. Vocabulary Alignment in Openly Specified Interactions

Author

Schorlemmer, Marco [0000-0002-9591-3325], Chocron, Paula, Schorlemmer, Marco, Schorlemmer, Marco [0000-0002-9591-3325], Chocron, Paula, and Schorlemmer, Marco

Abstract

The problem of achieving common understanding between agents that use different vocabularies has been mainly addressed by techniques that assume the existence of shared external elements, such as a meta-language or a physical environment. In this article, we consider agents that use different vocabularies and only share knowledge of how to perform a task, given by the specification of an interaction protocol. We present a framework that lets agents learn a vocabulary alignment from the experience of interacting. Unlike previous work in this direction, we use open protocols that constrain possible actions instead of defining procedures, making our approach more general. We present two techniques that can be used either to learn an alignment from scratch or to repair an existent one, and we evaluate their performance experimentally.

Published
2020

46. A computational framework for conceptual blending

Author

Eppe, Manfred, Maclean, Ewen, Confalonieri, Roberto, Kutz, Oliver, Schorlemmer, Marco, Plaza, Enric, Kühnberger, Kai-Uwe, Eppe, Manfred, Maclean, Ewen, Confalonieri, Roberto, Kutz, Oliver, Schorlemmer, Marco, Plaza, Enric, and Kühnberger, Kai-Uwe

Abstract

We present a computational framework for conceptual blending, a concept invention method that is advocated in cognitive science as a fundamental and uniquely human engine for creative thinking. Our framework treats a crucial part of the blending process, namely the generalisation of input concepts, as a search problem that is solved by means of modern answer set programming methods to find commonalities among input concepts. We also address the problem of pruning the space of possible blends by introducing metrics that capture most of the so-called optimality principles, described in the cognitive science literature as guidelines to produce meaningful and serendipitous blends. As a proof of concept, we demonstrate how our system invents novel concepts and theories in domains where creativity is crucial, namely mathematics and music., Deutscher Akademischer Austauschdienst (DAAD)

Published
2022

50. White Paper 11: Artificial intelligence, robotics & data science

Author

Marco de Lucas, Jesús Eugenio, Moreno-Arribas, M. Victoria, Degli Esposti, Sara, Sierra, Carles, Manyà, Felip, Colomé, Adrià, Osman, Nardine, López, Daniel, Ramasco, José J., Lloret Iglesias, Lara, Alenyà, Guillem, Villagrá, Jorge, del Castillo, M. Dolores, Schorlemmer, Marco, Noriega, Pablo, Ausín, Txetxu, Serrano, Teresa, Oyanguren, Arantza, Arroyo Guardeño, David, Brox, Piedad, and Arroyo Guardeño, David [0000-0001-8894-9779]

Abstract

198 p. : 17 cm, SIC white paper on Artificial Intelligence, Robotics and Data Science sketches a preliminary roadmap for addressing current R&D challenges associated with automated and autonomous machines. More than 50 research challenges investigated all over Spain by more than 150 experts within CSIC are presented in eight chapters. Chapter One introduces key concepts and tackles the issue of the integration of knowledge (representation), reasoning and learning in the design of artificial entities. Chapter Two analyses challenges associated with the development of theories –and supporting technologies– for modelling the behaviour of autonomous agents. Specifically, it pays attention to the interplay between elements at micro level (individual autonomous agent interactions) with the macro world (the properties we seek in large and complex societies). While Chapter Three discusses the variety of data science applications currently used in all fields of science, paying particular attention to Machine Learning (ML) techniques, Chapter Four presents current development in various areas of robotics. Chapter Five explores the challenges associated with computational cognitive models. Chapter Six pays attention to the ethical, legal, economic and social challenges coming alongside the development of smart systems. Chapter Seven engages with the problem of the environmental sustainability of deploying intelligent systems at large scale. Finally, Chapter Eight deals with the complexity of ensuring the security, safety, resilience and privacy-protection of smart systems against cyber threats., 18 EXECUTIVE SUMMARY ARTIFICIAL INTELLIGENCE, ROBOTICS AND DATA SCIENCE Topic Coordinators Sara Degli Esposti ( IPP-CCHS, CSIC ) and Carles Sierra ( IIIA, CSIC ) 18 CHALLENGE 1 INTEGRATING KNOWLEDGE, REASONING AND LEARNING Challenge Coordinators Felip Manyà ( IIIA, CSIC ) and Adrià Colomé ( IRI, CSIC – UPC ) 38 CHALLENGE 2 MULTIAGENT SYSTEMS Challenge Coordinators N. Osman ( IIIA, CSIC ) and D. López ( IFS, CSIC ) 54 CHALLENGE 3 MACHINE LEARNING AND DATA SCIENCE Challenge Coordinators J. J. Ramasco Sukia ( IFISC ) and L. Lloret Iglesias ( IFCA, CSIC ) 80 CHALLENGE 4 INTELLIGENT ROBOTICS Topic Coordinators G. Alenyà ( IRI, CSIC – UPC ) and J. Villagra ( CAR, CSIC ) 100 CHALLENGE 5 COMPUTATIONAL COGNITIVE MODELS Challenge Coordinators M. D. del Castillo ( CAR, CSIC) and M. Schorlemmer ( IIIA, CSIC ) 120 CHALLENGE 6 ETHICAL, LEGAL, ECONOMIC, AND SOCIAL IMPLICATIONS Challenge Coordinators P. Noriega ( IIIA, CSIC ) and T. Ausín ( IFS, CSIC ) 142 CHALLENGE 7 LOW-POWER SUSTAINABLE HARDWARE FOR AI Challenge Coordinators T. Serrano ( IMSE-CNM, CSIC – US ) and A. Oyanguren ( IFIC, CSIC - UV ) 160 CHALLENGE 8 SMART CYBERSECURITY Challenge Coordinators D. Arroyo Guardeño ( ITEFI, CSIC ) and P. Brox Jiménez ( IMSE-CNM, CSIC – US )

Published
2021

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