网络辅助答疑系统的设计与实现 - 论文发表 - 论文秘籍网 关键词：辅助答疑；关键字提取；关键字匹配 [gap=609]Key words: Assistant Reply; keywords drawing; keywords matching
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2 Unsupervised Classification, these keywords extraction algorithms that applies to a single document without using a corpus are presented, such as term frequency, based on SWN, the term graph, the term network.
本文主要研究基于词语网络的关键字提取算法,在分析已有基于词语网络的关键字提取算法的基础上,针对存在问题,提出一个新的基于词语网络的英文文档关键字提取策略,采用节点删除指标度量顶点(词语)的重要性。
参考来源 - 基于词语网络的关键字提取策略研究·2,447,543篇论文数据，部分数据来源于NoteExpress
该文描述的算法给出了基于层次词典的关键字提取和基于语料库的自动文摘的实现。
The algorithm given by the paper implements both keywording and abstracting while the former is based on a hierarchical dictionary and the latter on the corpus.
BLIMS系统包括信息自动分类与关键字提取子系统、信息自动文摘子系统和双语信息库BLIB及其存储与检索子系统。
There are three parts of BLIMS, i. e. auto-classifying and indexing system, auto-abstracting system, and BLIB storing and retrieving system.
关键字的提取将是一个手动进程，关键字的选择完全取决于执行选择的人。
The extraction of keywords would have been a manual process, their selection entirely at the mercy of the person performing it.
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