Anzeige
Erschienen in:
2013 | OriginalPaper | Buchkapitel
Exploratory Text Analysis: Data-Driven versus Human Semantic Similarity Judgments
verfasst von : Tiina Lindh-Knuutila, Timo Honkela
Erschienen in: Adaptive and Natural Computing Algorithms
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
We present an approach for comparing human-made and automatically generated semantic representations with an assumption that neither of these has a primary status over the other. In the experimental part, we compare the results gained by using independent component analysis and the self-organizing map algorithm on word context analysis with a semantically labeled dictionary called BLESS. The data-driven methods are useful in assessing the quality of the hand-created semantic resources and these resources can be used to evaluate the outcome of the automated process. We present a number of specific findings that go beyond typical quantitative evaluations of the results of data-driven methods in which the manually created resources are usually taken as a gold standard.