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Ontology Based Affective Context Representation

Published: 14 May 2007 Publication History

Abstract

In this paper we propose an ontology based representation of the affective states for context aware applications that allows expressing the complex relations that are among the affective states and between these and the other context elements. This representation is open to map different affective spaces; basic and secondary states relation (using Fuzzy Logic), the relation between these states and other context elements as location, time, person, activity etc. The proposed affective context model is encoded in OWL. Due to difficulties in direct detection of the secondary affective states we propose a method to infer the characteristic values of these states from other context elements values. The deduces states are used here to improve the behavior of a Context Aware Museum Guide in order to react more intuitively and more intelligent by taking into account the users affective states.

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cover image ACM Conferences
EATIS '07: Proceedings of the 2007 Euro American conference on Telematics and information systems
May 2007
498 pages
ISBN:9781595935984
DOI:10.1145/1352694
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 14 May 2007

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Author Tags

  1. affective computing
  2. context awareness
  3. logical inference
  4. ontology

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Overall Acceptance Rate 17 of 64 submissions, 27%

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Cited By

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  • (2023)Emotion Ontology Studies: A Framework for Expressing Feelings Digitally and its Application to Sentiment AnalysisACM Computing Surveys10.1145/355571955:9(1-38)Online publication date: 16-Jan-2023
  • (2022)Interdisciplinary IoT and Emotion Knowledge Graph-Based Recommendation System to Boost Mental HealthApplied Sciences10.3390/app1219971212:19(9712)Online publication date: 27-Sep-2022
  • (2022)Human Emotion: A Survey focusing on Languages, Ontologies, Datasets, and SystemsSN Computer Science10.1007/s42979-022-01116-x3:4Online publication date: 10-May-2022
  • (2021)Knowledge Engineering Framework for IoT Robotics Applied to Smart Healthcare and Emotional Well-BeingInternational Journal of Social Robotics10.1007/s12369-021-00821-615:3(445-472)Online publication date: 16-Nov-2021
  • (2019)Application of an Ontology-Based Platform for Developing Affective Interaction SystemsIEEE Access10.1109/ACCESS.2019.29034367(40503-40515)Online publication date: 2019
  • (2019)IAMHAPPY: Towards An IoT Knowledge-Based Cross-Domain Well-Being Recommendation System for Everyday HappinessSmart Health10.1016/j.smhl.2019.100083(100083)Online publication date: Dec-2019
  • (2018)Survey on ontologies for affective states and their influencesSemantic Web10.3233/SW-1702709:4(441-458)Online publication date: 1-Jan-2018
  • (2016)Ontology-Based Model for Mining User’s Emotions on the Wisdom WebWisdom Web of Things10.1007/978-3-319-44198-6_6(121-153)Online publication date: 8-Nov-2016
  • (2015)Emotions ontology for collaborative modelling and learning of emotional responsesComputers in Human Behavior10.1016/j.chb.2014.11.10051:PB(610-617)Online publication date: 1-Oct-2015
  • (2015)Electroencephalogram-based emotion assessment system using ontology and data mining techniquesApplied Soft Computing10.1016/j.asoc.2015.01.00730:C(663-674)Online publication date: 1-May-2015
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