Titlebook: Natural Language Understanding and Intelligent Applications; 5th CCF Conference o Chin-Yew Lin,Nianwen Xue,Yansong Feng Conference proceedi

非實體

muster

Tibetan Multi-word Expressions Identification Framework Based on News Corporasentences are segmented and high-frequency word-based n-grams are extracted using Nagao’s N-gram statistical algorithm and Statistical Substring Reduction Algorithm. In the second phase, the Tibetan MWEs are identified by the proposed framework which based on the combination of context analysis and

grudging

Building Powerful Dependency Parsers for Resource-Poor Languagese. Compared with the previous studies, our approach requires less human annotated resources. In our approach, we first train a POS tagger and a parser on the source treebank. Then, they are used to parse the source sentences in bilingual data. We obtain auto-parsed sentences (with POS tags and depen

BURSA

Bidirectional Long Short-Term Memory with Gated Relevance Network for Paraphrase Identificationudy of paraphrase identification. In this paper, we adopt a neural network model for paraphrase identification, called as bidirectional Long Short-Term Memory-Gated Relevance Network (Bi-LSTM+GRN). According to this model, a gated relevance network is used to capture the semantic interaction between

不透明

Syntactic Categorization and Semantic Interpretation of Chinese Nominal Compoundstic studies has gathered and established several syntactic categories of Nominal Compounds, which can be used for automatic syntactic categorization of these compounds. This paper is focused on Nominal Compounds of head-modifier construction because experiments show that most Nominal Compounds are h

空中

TDSS: A New Word Sense Representation Framework for Information Retrieval representing approaches often use only one view to represent a word, and may not work well in the tasks which are sensitive to the contexts, e.g., query rewriting. In this paper, we propose a new framework to represent a word sense simultaneously in two views, explanation view and context view. We

懶惰民族

A Word Vector Representation Based Method for New Words Discovery in Massive Textus into a new word vector representation with neural network model has shown a good performance in representing the original semantic relationship among words. Accordingly, the word vector representation is then introduced into the discovery of new word in Chinese text. In this work, we propose a ne

閑逛

Better Addressing Word Deletion for Statistical Machine Translationtion result. This paper studies how the word deletion problem can be handled in statistical machine translation (SMT) in detail. We classify this problem into . and . based on . and . words. Consequently, we propose four effective models to handle undesired word deletion. To evaluate word deletion p

occurrence

誘惑

Bilingual Parallel Active Learning Between Chinese and English achieving competitive performance. Previous studies on active learning are focused on corpora in one single language or two languages translated from each other. This paper proposes a Bilingual Parallel Active Learning paradigm (BPAL), where an instance-level parallel Chinese and English corpus ada