Automatic Text Summarization Approach Based on Textual Unit Association Networks
一种基于文本单元关联网络的自动文摘方法
Automatic text summarization is an important issue in Natural Language Processing.
自动文摘是自然语言处理领域的一项重要的研究课题。
A new computational scheme based on the combination of neighboring word is proposed,which is applied in automatic text summarization.
自动文摘技术应尽可能获取准确的相似度以确定句子或段落的权重,但目前常用的基于向量空间模型的计算方法却忽视句子、段落、文本中词的顺序。
Application in automatic abstracting for text clustering;
文本聚类在自动文摘中的应用研究
Text structure partition for automatic summarization;
面向自动文摘的文本结构划分
Research on Chinese automatic summarization based on user-query;
基于用户查询的中文自动文摘研究
Research on Chinese Automatic Summarization and Its Evaluation Method;
中文自动文摘及评价方法的研究
Since automatic abstraction is superior to manual abstraction for its speed,convenience,efficiency,and impersonality.
随着网络的发展,电子文本大量涌现,自动文摘以迅速、快捷、有效、客观等手工文摘无可比拟的优势,使得其实用价值得到充分体现。
We can find each sub theme which constitutes the theme of total text,and then realize automatic abstraction by taking such sub theme as the point of departure.
本文试图运用向量空间模型来确定文本段落之间内容的相关性 ,从而实现文本主题的自动分析 ,找出构成文本大主题的各个小主题 ,从这些小主题入手来实现自动文摘 ,可为自动文摘技术探索一条新途径。
This idea is useful not only in automatic abstraction,but also in automatic classification and document retrieval.
本文从自动文摘的需求出发 ,探讨特征词自动抽取的方法和技术 ,设计并实现了两种不同的特征词自动抽取算法。
We introduce the background and major contents of the comprehensive information theory and apply it to the research of automatic abstract in this paper.
该文介绍了全信息理论提出的背景及其主要内容，并将其应用到一种智能业务──自动文摘系统中，设计实现了一个基于理解的、面向神经网络学习算法领域的中文９动文摘系统 Ｌａｄｉｅｓ。
An understanding based Chinese automatic abstract system dedicated to a special field of neural networks learning algorithm (NNLA) is introduced in this paper, which is called LADIES (Literature Abstract and Digest Information Extract System).
自动文摘是计算机通信网提供智能业务的关键技术之一 。
The research of automatic abstract is an important and difficult point in the field of natural language processing.
自动文摘一直是自然语言处理领域研究的重点和难点。
The Research and Implementation of Single-document Chinese Text Summarization System
摘录式单文档中文自动文摘系统的研究与实现
A Study of Chinese Text Summarization Based on Adaptive Clustering Algorithm;
基于自适应聚类的中文自动文摘研究
Automatic Abstracting Based on English Texts:Technologies and Prospects;
基于英文文本的自动文摘:技术与展望
Research on the Som Based Automatic Text Summarization Approach;
基于自组织映射的自动文摘方法研究
Multi-document Summarization Based on Basic Element;
基于基本要素的多文档自动文摘研究
Multi-Documentation Summarization Based on LSA and pLSA
基于LSA和pLSA的多文档自动文摘
Automatic summarization system of a Chinese text based on conditional random field model
基于条件随机场的中文自动文摘系统
A Study of Chinese Multi-document Summarization Based on Adaptive Clustering Algorithm;
基于自适应聚类的中文多文档自动文摘研究
An Approach to Automatic Summarization by Integrating Latent Dirichlet Allocation in Conditional Random Field
一种基于LDA的CRF自动文摘方法
Evaluation method of automatic summarization based on semantic similarity
基于语义相似度的自动文摘评价方法
Query-Oriented Summarization Based on Genetic Algorithm
基于遗传算法的查询导向式自动文摘
Text Understand Based on Text Construction and Study On Automatic Abstraction System
自然语言篇章理解及基于理解的自动文摘研究
Research of Automatic Chinese Text Summarization Based on Feature Information Extract;
基于特征信息提取的中文自动文摘研究
Study on Chinese Text Automatic Summarization based on Concept Extension and Integrated Evaluation Method;
基于概念扩充和综合评价的中文自动文摘研究
Research of Chinese Text Automatic Summarization Based on Conceptual Vector Space Model;
基于概念向量空间模型的中文自动文摘研究
Research on Key Techniques of Query-focused Multi-document Summarization;
面向查询的多文档自动文摘关键技术研究
Research and Implementation of Topic-based Mutli-Document Summarization
基于主题的多文档自动文摘技术研究与实现
Research on Chinese Automatic Summarization Based on Clustering Algorithm
基于聚类算法的中文自动文摘方法研究