Selected publications in categories

Recent research areas and publications

Data-driven computational linguistics

Can machines learn the meaning of words and expressions from data? Contrary to what Chomsky claimed, much is possible and publications here discuss models of learning semantic relations.

Modeling subjectivity of meaning

Contrary to what early Wittgenstein claimed, each of us has a private language. In other words, each expression in any language is understood by each person in a different manner at least to a some degree. My “beautiful yellow house” does not look the same as yours. Logicians ran into trouble with their limited representations but continuous high-dimensional vectorial representations can be used to deal with intricacies of linguistic meaning.

Neural networks and statistical machine learning

Neural networks and machine learning methods based on biological inspiration or rigorous theoretical basis derived from probability theory, statistics and information theory are the cornerstones of modern data-driven information processing. In digital humanities, these methods are used for a wide range of tasks ranging from topic analysis to the study of historical processes. In humanities, an interesting challenge is the inherent presence of human interpretation. A critical view is necessary as no such thing as objective data exists.

Classical research areas and publications

Visual information retrieval and the WEBSOM method

Early word clouds: word category maps

Natural language database interface