Abstract. This paper describes an example-based machine translation (EBMT) method based on tree-string correspondence (TSC) and statistical generation. In this method, the translat...
In this paper we present a joint content selection and compression model for single-document summarization. The model operates over a phrase-based representation of the source doc...
We present a method for detecting and parsing buildings from unorganized 3D point clouds into a compact, hierarchical representation that is useful for high-level tasks. The input...
The paper presents a method of automatic enrichment of a very large dictionary of word combinations. The method is based on results of automatic syntactic analysis (parsing) of sen...
Alexander F. Gelbukh, Grigori Sidorov, Sang-Yong H...
We present the first unsupervised approach to the problem of learning a semantic parser, using Markov logic. Our USP system transforms dependency trees into quasi-logical forms, r...