Text Understanding

A novel approach to the problem of text understanding is presented, which exploits a distributed processing concept, where knowledge from different sources comes into play in the course of comprehension. …...

Language understanding work at Paramax focuses on ap- plying general-purpose language understanding technology to spoken language understanding, text understanding, and document processing, integrating language understanding with speech recognition, knowledge-based information …...

In this paper global patterns of thematic text organization me considered within the framework of a distributed model of text understmlding, ttased on file parsing resuhs of prior lext cohe- …...

Because of the complexity of documents and the variety of ap- plications which must be supported, document understand- ing requires the integration of image understanding with text understanding. Our docum(,nt …...

The discovery of semantic relations from text becomes increasingly important for applica- tions such as Question Answering, Informa- tion Extraction, Text Summarization, Text Un- derstanding, and others. The semantic rela- …...

Comparisons are common linguistic de- vices used to indicate the likeness of two things. Often, this likeness is not meant in the literal sense—for example, “I slept like a log” …...

AbstractDiscourse parsing is a popular technique widely used in text understanding, sentiment analysis and other NLP tasks. However, for most discourse parsers, the performance varies significantly across different discourse relations. …...

AbstractScript knowledge plays a central role in text understanding and is relevant for a variety of downstream tasks. In this paper, we consider two recent datasets which provide a rich …...

We present a new approach to evaluate computational models for the task of text understanding by the means of out-of-context error detection. Through the novel design of our automated modification …...

AbstractRecent studies show that integrating syntactic tree models with sequential semantic models can bring improved task performance, while these methods mostly employ shallow integration of syntax and semantics. In this …...