Natural language processing (NLP) went through a profound transformation in the mid-
1980s when it shifted to make heavy use of corpora and data-driven techniques to analyze …

Topic models provide insights into document collections, and their supervised extensions
also capture associated document-level metadata such as sentiment. However, inferring …

Words typically form the basis of psycholinguistic and computational linguistic studies about
sentence processing. However, recent evidence shows the basic units during reading, ie …

Web search queries provide a surprisingly large amount of information, which can be
potentially organized and converted into a knowledgebase. In this paper, we focus on the …

This paper attempts to discover communication patterns automatically within dog
vocalizations in a data-driven approach, which breaks the barrier previous approaches that …

Electroencephalography (EEG) is a suitable non-invasive measure for investigating the
temporal dynamics of mental processing because of its high temporal resolution and cost …

Derivational nouns are widely used in Sanskrit corpora and represent an important
cornerstone of productivity in the language. Currently there exists no analyser that identifies …

To support IT change automation in cloud-native deployments, we propose to discover
change actions from IT change requests. Traditional approaches to discover actions rely on …

This work presents the use of Adaptor Grammar, a nonparametric Bayesian approach for
learning (Probabilistic) Context-Free Grammar productions from data. In Adaptor Grammar …

Image memes (simply memes) are becoming increasingly popular over social media. In this
work, we for the first time, investigate the evolution and life-cycle of an online community that …