Automated Model of Comprehension V2.0

Dragos Georgian Corlatescu, Mihai Dascalu, Danielle S. McNamara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


Reading comprehension is key to knowledge acquisition and to reinforcing memory for previous information. While reading, a mental representation is constructed in the reader’s mind. The mental model comprises the words in the text, the relations between the words, and inferences linking to concepts in prior knowledge. The automated model of comprehension (AMoC) simulates the construction of readers’ mental representations of text by building syntactic and semantic relations between words, coupled with inferences of related concepts that rely on various automated semantic models. This paper introduces the second version of AMoC that builds upon the initial model with a revised processing pipeline in Python leveraging state-of-the-art NLP models, additional heuristics for improved representations, as well as a new radiant graph visualization of the comprehension model.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Education - 22nd International Conference, AIED 2021, Proceedings
EditorsIdo Roll, Danielle McNamara, Sergey Sosnovsky, Rose Luckin, Vania Dimitrova
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages5
ISBN (Print)9783030782696
StatePublished - 2021
Event22nd International Conference on Artificial Intelligence in Education, AIED 2021 - Virtual, Online
Duration: Jun 14 2021Jun 18 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12749 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference22nd International Conference on Artificial Intelligence in Education, AIED 2021
CityVirtual, Online


  • Comprehension model
  • Lexical dependencies
  • Natural language processing
  • Semantic links

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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