期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：8
页码：333-340
出版社：Science and Information Society (SAI)
摘要：Autonomous intelligent agents have become a very
important research area in Artificial Intelligence (AI). Sociocultural
situations are one challenging area in which autonomous
intelligent agents can acquire new knowledge or modify existing
one. Socio-cultural situations can be best represented in the form
of cognitive scripts that can allow different techniques to be used
to facilitate knowledge transfer between scripts. Conceptual
blending has proven successful in enhancing the social dynamics
of cognitive scripts, where information is transferred from
similar contextual scripts to a target script resulting in a new
blended script. To the extent of our knowledge, there is no
computational model available to evaluate these newly generated
cognitive scripts. This work aims to develop a computational
model to evaluate cognitive scripts resulting from blending two
or more linear cognitive scripts. The evaluation process involves:
1) using the GloVe similarity to check if the transferred events
conceptually fit the target script; 2) using the semantic view of
text coherence to decide on the optimal position(s) to place the
transferred event(s) in the target script. Results show that the
GloVe similarity can be applied successfully to preserve the
contextual meaning of cognitive scripts. Additional results show
that GloVe embedding gives higher accuracy over Universal
Sentence Encoder (USE) and Smooth Inverse Frequency (SIF)
embedding but this comes with a high computational cost. Future
work will look into reducing the computational cost and
enhancing the accuracy.
