This article delves into the scoring function of the statistical paraphrase generation model. It presents an algorithm for exact computation and two applicative experiments. The f...
Position information has been proved to be very effective in document summarization, especially in generic summarization. Existing approaches mostly consider the information of se...
In this paper, we present an unsupervised hybrid model which combines statistical, lexical, linguistic, contextual, and temporal features in a generic EMbased framework to harvest...
We present an adaptation technique for statistical machine translation, which applies the well-known Bayesian learning paradigm for adapting the model parameters. Since state-of-t...
In the field of multi-document summarization, the Pyramid method has become an important approach for evaluating machine-generated summaries. The method is based on the manual ann...
Leonhard Hennig, Ernesto William De Luca, Sahin Al...
Phrase-based statistical MT (SMT) is a milestone in MT. However, the translation model in the phrase based SMT is structure free which greatly limits its reordering capacity. To a...
Shui Liu, Sheng Li, Tiejun Zhao, Min Zhang, Pengyu...
We present a new method, based on graph theory, for bilingual lexicon extraction without relying on resources with limited availability like parallel corpora. The graphs we use re...
The aim of this study is to use the word-space model to measure the semantic loads of single verbs, profile verbal lexicon acquisition, and explore the semantic information on Chi...
Recent work on distributional methods for similarity focuses on using the context in which a target word occurs to derive context-sensitive similarity computations. In this paper ...