Statistical Approaches

The identification of semantically related terms for a given word is an important problem. A number of statistical approaches have been proposed to ad- dress this problem. Most approaches draw …...

Dictionary-based translation is a traditional approach in use by cross-language information retrieval systems. However, significant performance degradation is often observed when queries contain words that do not appear in the …...

AbstractGrammatical approaches to language technology are often considered less optimal than statistical approaches in multilingual settings, where large-scale portability becomes an important issue. The present paper argues that there is …...

. Statistical approaches used in machine translation (MT) require the availability of large parallel corpora for the task at hand. The relative scarcity of thes resources makes domain adaptation a …...

AbstractHighly frequent in language and communication, metaphor represents a significant challenge for Natural Language Processing (NLP) applications. Computational work on metaphor has traditionally evolved around the use of hand-coded knowledge, …...

AbstractTexts from the Internet serve as important data sources for financial market modeling. Early statistical approaches rely on manually defined features to capture lexical, sentiment and event information, which suffers …...

AbstractThe state of the art in machine translation (MT) is governed by neural approaches, which typically provide superior translation accuracy over statistical approaches. However, on the closely related task of …...

AbstractSpoken language understanding (SLU), which converts user requests in natural language to machine-interpretable expressions, is becoming an essential task. The lack of training data is an important problem, especially for …...