Heather Maclaren
Artificial Intelligence · 2009
A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 13 citations into it; #14,086 of 35,345 by trust here, #23,731 by citations
- Social Psychology — 8 citations into it
- Experimental and Cognitive Psychology — 5 citations into it
Whom Heather Maclaren trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David E. Heckerman
- Cristina Conati
- P. Lachenbruch
- Patrick Gebhard
- Rosalind W. Picard
- Ashish Kapoor
- João Dias
- Regan L. Mandryk
- Jennifer A. Healey
- Ana Paiva
Who trusts Heather Maclaren overall
- S. D’Mello
- Konstantina Chrysafiadi
- Michel C. Desmarais
- A. Graesser
- Ryan Shaun Joazeiro de Baker
- Maria K. Virvou
Papers from Heather Maclaren's perspective
Ordered by how strongly the researchers Heather Maclaren trusts endorse each paper. Same corpus, a different order for every researcher.
- Toward Machine Emotional Intelligence: Analysis of Affective Physiological State (IEEE Transactions on Pattern Analysis and Machine Intelligence)
- Probabilistic assessment of user's emotions in educational games (Applied Artificial Intelligence)
- Multimodal affect recognition in learning environments (ACM Multimedia)
- Affect and learning: An exploratory look into the role of affect in learning with AutoTutor
- A domain-independent framework for modeling emotion (Cognitive Systems Research)
- Machine learning in automated text categorization
- Detecting stress during real-world driving tasks using physiological sensors (IEEE transactions on intelligent transportation systems (Print))
- Using psychophysiological techniques to measure user experience with entertainment technologies (Behavior and Information Technology)
- Predicting Student Emotions in Computer-Human Tutoring Dialogues
- Feeling and Reasoning: A Computational Model for Emotional Characters (Portuguese Conference on Artificial Intelligence)
Their papers
- Empirically building and evaluating a probabilistic model of user affect (2009) — 364 citations