Posts by Collection

portfolio

publications

Hierarchical Organization of Segmentation in Non-Functional Action Sequences

Published in Journal for the Cognitive Science of Religion, 2013

Event segmentation of cultural behaviors

Recommended citation: Nielbo, K.L., Schjoedt, U. & Sørensen, J. (2013). "Hierarchical Organization of Segmentation in Non-Functional Action Sequences." Journal for the Cognitive Science of Religion. 1(1).

Prediction Error During Functional and Non-Functional Action Sequences: A Computational Exploration of Ritual and Ritualized Event Processing

Published in Journal of Cognition and Culture, 2013

Computer simulation of human action perception under cultural influence

Recommended citation: Nielbo, K.L. & Sørensen, J. (2013). "Prediction Error During Functional and Non-Functional Action Sequences: A Computational Exploration of Ritual and Ritualized Event Processing." Journal of Cognition and Culture. 13.

talks

Tutorial in Text & Data Mining w. Python

Published:

The recent explosion in digitized and digital text-media is rapidly changing the evidential basis for the humanities. While the humanities used to be the principal scientific consumers of text-based data, the majority of text analysis is now performed by ‘machines’ outside traditional humanistic domains. Text & Data Mining (TDM) applies machine learning in order to extract useful knowledge from from large collections of linguistic data. This workshop will showcase multiple techniques for building TDM tools based on the popular programming language Python.

Tutorial in Text & Data Mining w. Python

Published:

DESCRIPTION

The recent explosion in digitized and digital text-media is rapidly changing the evidential basis for the humanities. While the humanities used to be the principal scientific consumers of text-based data, the majority of text analysis is now performed by ‘machines’ outside traditional humanistic domains. Text-Analytics applies automated and data-intensive techniques in order to extract useful knowledge from from large collections of linguistic data. In this PhD course, the participant will acquire experience with two major machine learning paradigms (supervised and unsupervised learning) in order to answer research questions fundamental to the humanities: can we classify texts by genres, periods and status and how do surface structures reveal latent semantic properties. The workshop consists of a series of hands-on tutorials with Python combined with useful explanations and illustrations through use-cases. Programming experience is not a requirement, but participants are should to prepare by installing Python and completing three introductory tutorials available on-line.

teaching

Text-Mining the Great Unread

Under-graduate and graduate course, Aarhus University, School of Culture and Society, 2017

Three weeks intensive course about text-mining, natural language processing and information retrieval with Python and Unix.

Text-Mining Bootcamp

Postgraduate course, Dansk Sprog og Litteraturselskab & University of Copenhagen, 2017

Five days hands-on workshop about text-mining literature with Python. Curriculum, slides and code samples are avaialbe in GitHub repository: Repository here