This paper describes an attempt to devise a knowledge discovery model that is inspired from the two theoretical frameworks of selectionism and constructivism in human cognitive le...
We present a probabilistic generative model for learning semantic parsers from ambiguous supervision. Our approach learns from natural language sentences paired with world states ...
Abstract. The presence of long gaps dramatically increases the difficulty of detecting and characterizing complex events hidden in long sequences. In order to cope with this proble...
In Chinese, phrases and named entities play a central role in information retrieval. Abbreviations, however, make keyword-based approaches less effective. This paper presents an em...
In biomedical articles, terms with the same surface forms are often used to refer to different entities across a number of model organisms, in which case determining the species b...