Context Matters: Recovering Human Semantic Structure from Machine Learning Analysis of Large‐Scale Text Corpora

, , , &
Cognitive Science 46 (2):e13085 (2022)
  Copy   BIBTEX

Abstract

Cognitive Science, Volume 46, Issue 2, February 2022.

Categories

Add categories

Keywords

Reprint years

DOI

10.1111/cogs.13085

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 91,386

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

My notes

Similar books and articles

Context Matters: Recovering Human Semantic Structure from Machine Learning Analysis of Large‐Scale Text Corpora.Marius Cătălin Iordan, Tyler Giallanza, Cameron T. Ellis, Nicole M. Beckage & Jonathan D. Cohen - 2022 - Cognitive Science 46 (2):e13085.
Concept Representation Analysis in the Context of Human-Machine Interactions.Farshad Badie - 2016 - In 14th International Conference on e-Society. pp. 55-61.
A Conceptual Framework Over Contextual Analysis of Concept Learning Within Human-Machine Interplays.Farshad Badie - 2017 - In Emerging Technologies for Education. Cham, Switzerland: pp. 65-74.
Unsupervised learning and grammar induction.Alex Clark & Shalom Lappin - unknown
Latent semantic analysis (LSA), a disembodied learning machine, acquires human word meaning vicariously from language alone.Thomas K. Landauer - 1999 - Behavioral and Brain Sciences 22 (4):624-625.
Playing with machines: Using machine learning to understand automated copyright enforcement at scale.Nicolas P. Suzor & Joanne E. Gray - 2020 - Big Data and Society 7 (1).
A Large‐Scale Analysis of Variance in Written Language.Brendan T. Johns & Randall K. Jamieson - 2018 - Cognitive Science 42 (4):1360-1374.
Can Machine Learning Provide Understanding? How Cosmologists Use Machine Learning to Understand Observations of the Universe.Helen Meskhidze - 2023 - Erkenntnis 88 (5):1895-1909.
Computational Methods to Extract Meaning From Text and Advance Theories of Human Cognition.Danielle S. McNamara - 2011 - Topics in Cognitive Science 3 (1):3-17.
Deep learning approach to text analysis for human emotion detection from big data.Jia Guo - 2022 - Journal of Intelligent Systems 31 (1):113-126.
The virtue of simplicity: On machine learning models in algorithmic trading.Kristian Bondo Hansen - 2020 - Big Data and Society 7 (1).
Human Semi-Supervised Learning.Bryan R. Gibson, Timothy T. Rogers & Xiaojin Zhu - 2013 - Topics in Cognitive Science 5 (1):132-172.
The Large‐Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic Growth.Mark Steyvers & Joshua B. Tenenbaum - 2005 - Cognitive Science 29 (1):41-78.
Machine learning: A structuralist discipline?Christophe Bruchansky - 2019 - AI and Society 34 (4):931-938.
Machine learning: A structuralist discipline?Christophe Bruchansky - 2019 - AI and Society 34 (4):931-938.

Analytics

Added to PP
2022-02-25

Downloads
17 (#846,424)

6 months
9 (#290,637)

Historical graph of downloads
How can I increase my downloads?

Author's Profile

Jonathan Cohen
University of South Carolina

Citations of this work

No citations found.

Add more citations

References found in this work

Features of similarity.Amos Tversky - 1977 - Psychological Review 84 (4):327-352.
An Integrative Theory of Prefrontal Cortex Function.Earl K. Miller & Jonathan D. Cohen - 2001 - Annual Review of Neuroscience 24 (1):167-202.
Principles of categorization [Електронний ресурс]/Eleonora Rosch.E. Rosch - 1978 - In Eleanor Rosch & Barbara Lloyd (eds.), Cognition and Categorization. Lawrence Elbaum Associates.

View all 13 references / Add more references