Besides, the algorithm can dynamically obtain the proper document summarization length.
同时该方法能动态地确定文档摘要长度。
Automatic multi-document summarization is an outgrowth of single document summarization.
文本自动综述是自动文摘在多文档上的推广。
In this paper, we propose an approach to achieve a system for query-focused multi-document summarization.
针对面向查询的多文档自动文摘，本文提出了一种系统实现方法。
The multi-document summarization technology is becoming a research focus in the field of natural language processing.
多文档自动文摘技术日益成为自然语言处理领域的一个研究热点。
In order to solve the greatly dimension of word frequency and sparse matrix, this paper proposes a multi-document summarization method based on sub-topics area partition.
为解决词频矩阵的词频维数过大和矩阵过于稀疏的问题，提出一种子主题区域划分的多文档自动文摘方法。
The research can be summarized as follows:Firstly, for query-focus multi-document summarization, this paper proposed the strategy of summary sentence selection using keywords extraction.
本文的主要工作包括以下几个方面：第一，本文提出了一种以关键词语抽取为核心的文摘句选择策略。
Sentence similarity computation is very important in all the fields of Natural Language Processing. In Multi-document Summarization Technology, sentence similarity computation is a key problem.
句子间相似度的计算在自然语言处理的各个领域都占有很重要的地位，在多文档自动文摘技术中，句子间相似度的计算是一个关键的问题。
The pipeline processes documents before they are indexed in the full-text index, and it provides automated summarization, document format conversion, and categorization services (See Figure 1).
在全文索引中建立文档的索引之前，管道将对文档进行处理，并且提供了自动化的摘要、文档格式转换和分类服务（请参见图1）。
Automatic text summarization provides a concise summary for a document.
自动文本摘要的文档提供了一个简明的总结。
Automatic text summarization provides a concise summary for a document.
自动文本摘要的文档提供了一个简明的总结。
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