This paper is concerned with data selection for adapting language model (LM) in statistical machine translation (SMT), and aims to find the LM training sentences that are topic similar to the translation task. Although the traditional approaches have gained significant performance, they ignore the topic information and the distribution information of words when selecting similar training senten...

Abstract The annual number of publications at scientific venues, for example, conferences and journals, is growing quickly. Hence, even researchers it becomes harder to keep track research topics their progress. In this task, can be supported by automated publication analysis. Yet, many such methods result in uninterpretable, purely numerical representations. As an attempt support human analyst...

This paper focuses on enhancing the effectiveness of filter feature selection models from two aspects. First, feature-searching engine is modified based on optimization theory. Second, a point injection strategy is designed to improve the regularization capability of feature selection. The second topic is important, because overfitting is usually experienced. To evaluate the proposed strategies...