A Study of the Probability Distribution and Grammatical Collocation Patterns of Multi-Category Words in Chinese Information Processing

2021 ◽  
Vol 09 (02) ◽  
pp. 524-529
Author(s):  
浩学 王
Keyword(s):  
Information Processing ◽  
Probability Distribution ◽  
Chinese Information Processing

Research on Sustainable Mining Engineering

2013 ◽  
Vol 340 ◽  
pp. 126-130 ◽  
Author(s):  
Xiao Guang Yue ◽  
Guang Zhang ◽  
Qing Guo Ren ◽  
Wen Cheng Liao ◽  
Jing Xi Chen ◽  
...  
Keyword(s):  
Information Processing ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Social Economy ◽  
Scientific Research ◽  
The Other ◽  
Mining Engineering ◽  
Chinese Information Processing ◽  
Development Tendency

The concepts of Chinese information processing and natural language processing (NLP) and their development tendency are summarized. There are different comprehension of Chinese information processing and natural language processing in China and the other countries. But the work appears to emerge in the study of key point of languages processing. Mining engineering is very important for our country. Though the final task of languages processing is difficult, Chinese information processing has contributed substantially to our scientific research and social economy and it will play an important part for mining engineering in our future.

Overview of Chinese Word Segmentation Method

2013 ◽  
Vol 427-429 ◽  
pp. 2568-2571
Author(s):  
Shu Xian Liu ◽  
Xiao Hua Li
Keyword(s):  
Information Processing ◽  
Natural Language Processing ◽  
Language Processing ◽  
Word Segmentation ◽  
Basic Knowledge ◽  
Chinese Characters ◽  
Chinese Word ◽  
Segmentation Method ◽  
Chinese Word Segmentation ◽  
Chinese Information Processing

This article provides a brief introduction to Natural Language Processing and basic knowledge of Chinese Word Segmentation at first. Chinese Word Segmentation is a process of turning a series of Chinese characters into a series of Chinese words with some rules. As the fundamental component of Chinese information processing, it is wildly used in correlative areas. Accordingly, research on Chinese Word Segmentation has important theoretic and realistic meaning. In this paper, we mainly introduces the challenge in Chinese Word Segmentation, and presented the categories of Chinese Word Segmentation method.

HTRDP evaluations on Chinese information processing and intelligent human-machine interface

2007 ◽  
Vol 1 (1) ◽  
pp. 58-93 ◽  
Author(s):  
Qun Liu ◽  
Xiangdong Wang ◽  
Hong Liu ◽  
Le Sun ◽  
Sheng Tang ◽  
...  
Keyword(s):  
Information Processing ◽  
Human Machine Interface ◽  
Chinese Information Processing ◽  
Machine Interface

Chinese New Word Identification Using N-Gram and PPM Models

2011 ◽  
Vol 109 ◽  
pp. 612-616 ◽  
Author(s):  
Dun Li ◽  
Wei Tu ◽  
Lei Shi
Keyword(s):  
Information Processing ◽  
Word Identification ◽  
Recall Rate ◽  
Word Segmentation ◽  
Experimental Results ◽  
New Method ◽  
New Words ◽  
Chinese Information Processing ◽  
N Gram

New word identification is one of the difficult problems of the Chinese information processing. This paper presents a new method to identify new words. First of all, the text is segmented using N-Gram; then PPM is used to identify the new words which are in the text; finally, the new identified words are added to update the dictionary using LRU. Compared with three well-known word segmentation systems, the experimental results show that this method can improve the precision and recall rate of new word identification to a certain extent.

Learning Hierarchical Lexical Hyponymy

2012 ◽  
pp. 205-219
Author(s):  
Jiayu Zhou ◽  
Shi Wang ◽  
Cungen Cao
Keyword(s):  
Information Processing ◽  
Machine Translation ◽  
Large Scale ◽  
Computational Approach ◽  
Experimental Results ◽  
Ontology Learning ◽  
Linguistic Features ◽  
Critical Step ◽  
Chinese Information Processing ◽  
Novel Approach

Chinese information processing is a critical step toward cognitive linguistic applications like machine translation. Lexical hyponymy relation, which exists in some Eastern languages like Chinese, is a kind of hyponymy that can be directly inferred from the lexical compositions of concepts, and of great importance in ontology learning. However, a key problem is that the lexical hyponymy is so commonsense that it cannot be discovered by any existing acquisition methods. In this paper, we systematically define lexical hyponymy relationship, its linguistic features and propose a computational approach to semi-automatically learn hierarchical lexical hyponymy relations from a large-scale concept set, instead of analyzing lexical structures of concepts. Our novel approach discovered lexical hyponymy relation by examining statistic features in a Common Suffix Tree. The experimental results show that our approach can correctly discover most lexical hyponymy relations in a given large-scale concept set.

The Review of Automatic Chinese Word Segmentation

2014 ◽  
Vol 701-702 ◽  
pp. 386-389 ◽  
Author(s):  
Xiao Yan Ren ◽  
Yun Xia Fu
Keyword(s):  
Information Processing ◽  
Formal Model ◽  
Word Segmentation ◽  
Chinese Word ◽  
Chinese Word Segmentation ◽  
Research Status ◽  
Chinese Information Processing ◽  
Great Progress

As the fundamental work of Chinese information processing, Chinese word segmentation has achieved great progress since its birth. This paper reviews the research status of the CWS, discusses the formal model of automatic word segmentation, and analyzes the difficulties of word segmentation.

scholarly journals Exponential Negation of a Probability Distribution

2021 ◽  
Author(s):  
Qinyuan Wu ◽  
Yong Deng ◽  
Neal Xiong
Keyword(s):  
Information Processing ◽  
Probability Distribution ◽  
Uniform Distribution ◽  
Probability Distributions ◽  
Numerical Examples ◽  
Entropy Increase ◽  
Intelligent Information Processing ◽  
Uniform Probability Distribution ◽  
Intelligent Information ◽  
Number Of Iterations

Abstract Negation operation is important in intelligent information processing. Different with existing arithmetic negation, an exponential negation is presented in this paper. The new negation can be seen as a kind of geometry negation. Some basic properties of the proposed negation are investigated, we find that the fix point is the uniform probability distribution. The proposed exponential negation is an entropy increase operation and all the probability distributions will converge to the uniform distribution after multiple negation iterations. The convergence speed of the proposed negation is also faster than the existed negation. The number of iterations of convergence is inversely proportional to the number of elements in the distribution. Some numerical examples are used to illustrate the efficiency of the proposed negation.

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