CALL FOR PAPERS
DiDaS 2012 – 1st Workshop on Distributional Data Semantics
September 21, 2012, Palermo, Italy
at the 6th IEEE International Conference on Semantic Computing (ICSC)
Efficient means for capturing and representing computational semantics of data are critical for coping with current limitations of information systems, especially if one wants to make sense of large amounts of information coming from heterogeneous and/or poorly structured resources. Efforts aimed at representing meaning of data in a machine-readable way (i.e., Semantic Web or deductive databases) have achieved some level of success. There are alternatives to the top-down, assertional approaches to semantics, which can work even without (too much) expensive human involvement. One of the most widely and successfully used are distributional semantics models that have been researched within the field of computational linguistics. These models, based on the distributional hypothesis, provide a bottom-up approach to the computational representation of meaning, where the statistical co-occurrence of words in unstructured corpora can provide a basis for the construction of simplified but comprehensive and extensible models of semantic content.