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Location extraction from tweets
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In: ISSN: 0306-4573 ; Information Processing and Management ; https://hal.archives-ouvertes.fr/hal-02640811 ; Information Processing and Management, Elsevier, 2018, 54 (2), pp.129-144. ⟨10.1016/j.ipm.2017.11.001⟩ (2018)
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| 103 |
Attribution and Artificial Intelligence: Embedding Provenance with Material Metadata
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In: Architecture Publications (2018)
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| 104 |
Special issue on Sensing, Data Analysis and Platforms for Ubiquitous Intelligence
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| 105 |
The Relation of Personality and Intelligence—What Can the Brunswik Symmetry Principle Tell Us?
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In: Journal of Intelligence ; Volume 6 ; Issue 3 (2018)
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| 106 |
The Great Debate: General Ability and Specific Abilities in the Prediction of Important Outcomes
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In: Journal of Intelligence ; Volume 6 ; Issue 3 (2018)
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| 107 |
The Relation of Personality and Intelligence—What Can the Brunswik Symmetry Principle Tell Us?
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| 108 |
Semantic reranking of CRF label sequences for verbal multiword expression identification ; Multiword expressions at length and in depth: Extended papers from the MWE 2017 workshop
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| 109 |
Precision immunoprofiling by image analysis and artificial intelligence
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| 110 |
Enhancing Your Intelligence Agency Information Resource IQ: PT. 1: The Office of the Director of National Intelligence
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In: Libraries Faculty and Staff Presentations (2018)
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| 111 |
Troping the Enemy: Metaphor, Culture, and the Big Data Black Boxes of National Security
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In: Secrecy and Society (2018)
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| 112 |
The relation of personality and intelligence - what can the Brunswik symmetry principle tell us?
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| 113 |
A Semi-supervised Corpus Annotation for Saudi Sentiment Analysis Using Twitter
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| 114 |
Pensamiento crítico de los jóvenes ciudadanos frente a las noticias en Chile
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In: Comunicar: Revista científica iberoamericana de comunicación y educación, ISSN 1134-3478, Nº 54, 2018, pags. 101-110 (2018)
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| 117 |
ImproteK: introducing scenarios into human-computer music improvisation
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In: ACM Computers in Entertainment ; https://hal.archives-ouvertes.fr/hal-01380163 ; ACM Computers in Entertainment, 2017, ⟨10.1145/3022635⟩ (2017)
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Abstract:
International audience ; This article focuses on the introduction of control, authoring, and composition in human-computer music improvisation through the description of a guided music generation model and a reactive architecture, both implemented in the software ImproteK. This interactive music system is used with expert improvisers in work sessions and performances of idiomatic and pulsed music, and more broadly in situations of structured or composed improvisation. The article deals with the integration of specifications in the music generation process by means of a fixed or dynamic "scenario", and addresses the issue of the dialectic between reactivity and planning in interactive music improvisation. It covers the different levels involved in the machine improvisation: the integration of anticipation relative to a predefined structure in a guided generation process at a symbolic level, an architecture combining this anticipation with reactivity using mixed static/dynamic scheduling techniques, and an audio rendering module performing live re-injection of captured material in synchrony with a non-metronomic beat. Finally, it sketches a framework to compose improvisation sessions at the scenario level, extending the initial musical scope of the system. All these points are illustrated by videos of performances or work sessions with musicians.
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Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]; [INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]; [INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]; [INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD]; [SHS.MUSIQ]Humanities and Social Sciences/Musicology and performing arts; Abstraction; ACM: D.: Software/D.4: OPERATING SYSTEMS/D.4.7: Organization and Design/D.4.7.4: Real-time systems and embedded systems; ACM: F.: Theory of Computation/F.2: ANALYSIS OF ALGORITHMS AND PROBLEM COMPLEXITY/F.2.2: Nonnumerical Algorithms and Problems/F.2.2.3: Pattern matching; ACM: H.: Information Systems/H.5: INFORMATION INTERFACES AND PRESENTATION (e.g.; ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.11: Distributed Artificial Intelligence/I.2.11.1: Intelligent agents; ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.8: Problem Solving; ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.5: Structural; ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.4: Applications/I.5.4.1: Signal processing; and processing; and Search/I.2.8.4: Heuristic methods; Combinatorics on words; Control Methods; HCI)/H.5.5: Sound and Music Computing/H.5.5.1: Modeling; HCI)/H.5.5: Sound and Music Computing/H.5.5.2: Signal analysis; HCI)/H.5.5: Sound and Music Computing/H.5.5.3: Systems; Heuristic function construction; Intelligent agents; Markov processes; modeling and modularity; Modeling methodologies; Motif discovery; Music retrieval; Performing arts; Planning under uncertainty; Real-time system architecture; Sound and music computing; Symbolic and algebraic algorithms; synthesis
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URL: https://hal.archives-ouvertes.fr/hal-01380163/file/ACM-CiE_ImproteK_Nika-et-al_2017.pdf
https://doi.org/10.1145/3022635
https://hal.archives-ouvertes.fr/hal-01380163/document
https://hal.archives-ouvertes.fr/hal-01380163
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| 118 |
Facial Expression Emotion Detection for Real-time Embedded Systems
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| 119 |
FrenchSentiClass : an Automated System for French Sentiment Classification ; FrenchSentiClass : un Système Automatisé pour la Classification de Sentiments en Français
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In: Actes de l’atelier DEFT de la conférence TALN 2017 ; DEFT: Défi Fouille de Texte ; https://hal-lirmm.ccsd.cnrs.fr/lirmm-01563411 ; DEFT: Défi Fouille de Texte, Jun 2017, Orléans, France (2017)
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| 120 |
La cartographie des traces textuelles comme méthodologie d’enquête en sciences sociales
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In: https://hal-sciencespo.archives-ouvertes.fr/tel-03626011 ; Sociologie. École normale supérieure, 2017 (2017)
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