[1]王占一,徐蔚然,郭军.智能文本搜索新技术[J].智能系统学报,2012,7(1):40-49.
　WANG Zhanyi,XU Weiran,GUO Jun.New technologies of intelligent text search[J].CAAI Transactions on Intelligent Systems,2012,7(1):40-49.
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智能文本搜索新技术

《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷: 7 期数: 2012年第1期 页码: 40-49 栏目: 学术论文—自然语言处理与理解 出版日期: 2012-02-25
Title:
New technologies of intelligent text search
文章编号:
1673-4785(2012)01-0040-10
作者:
王占一1,2，徐蔚然1,2，郭军1,2
1.北京邮电大学 模式识别与智能系统实验室，北京 100876；
2.北京邮电大学 信息与通信工程学院，北京 100876
Author(s):
WANG Zhanyi1,2, XU Weiran1,2, GUO Jun1,2
1. Pattern Recognition and Intelligent System (PRIS) Laboratory, Beijing University of Posts and Telecommunications, Beijing 100876, China;
2. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
关键词:
智能文本搜索; 文本检索; 文本分析
Keywords:
intelligent text search;  text retrieval;  text analysis
分类号:
TP393
文献标志码:
A
摘要:
面对当今互联网上海量的信息，以及搜索信息准确、高效、个性化等需求，提出了一套包括信息检索、信息抽取和信息过滤在内的智能文本搜索新技术.首先举荐了与信息检索新技术相关的企业检索、实体检索、博客检索、相关反馈子任务.然后介绍了与信息抽取技术相关的实体关联和实体填充子任务，以及与信息过滤技术相关的垃圾邮件过滤子任务.这些关键技术融合在一起，在多个著名的国际评测中得到应用，如美国主办的文本检索会议评测和文本分析会议评测，并且在互联网舆情、短信舆情和校园网对象搜索引擎等实际系统中得到了检验.
Abstract:
To adapt to the massive amount of information on the internet and the need for accuracy, efficiency, and individualization, a set of technologies of intelligent text search including information retrieval, extraction, and filtering were proposed. First, new technologies of information retrieval were illustrated including the subtasks of enterprise retrieval, entity retrieval, blog retrieval, and relevance feedback. Second, the subtask of entity linking and slot filling related to information extraction was introduced. Finally, the subtask of spam email filtering related to information filtering was described. These technologies were converged for application in many wellknown international evaluations. These include the text retrieval conference (TREC) and text analysis conference (TAC) sponsored in the USA, and these technologies of intelligent text search were proven in practical applications such as public opinions on the Internet, short message opinions, and the campus object search engine (COSE).
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相似文献/References:
[1]邸剑,刘骏华,曹锦纲.利用BERT和覆盖率机制改进的HiNT文本检索模型[J].智能系统学报,2024,19(3):719.[doi:10.11992/tis.202201020]
　DI Jian,LIU Junhua,CAO Jingang.An improved HiNT text retrieval model using BERT and coverage mechanism[J].CAAI Transactions on Intelligent Systems,2024,19():719.[doi:10.11992/tis.202201020]

备注/Memo

收稿日期： 2011-01-02.
网络出版时间： 2012-02-18.
基金项目：国家自然科学基金资助项目(60905017)；高等学校学科创新引智计划项目(B08004). 
通信作者：王占一.???????? E-mail：wangzhanyi@gmail.com.
作者简介：
王占一，男，1984年生，博士研究生，主要研究方向为信息过滤和信息检索等.在国内外重要期刊和会议上发表学术论文10篇，获发明专利2项.
?徐蔚然，男，1975年生，副教授，主要研究方向为信息检索、模式识别和机器学习.主持参加了TREC、TAC、ACE等国际著名检索评测，并且获得优异成绩，参与多项国家级科研项目，发表学术论文20余篇.
郭军，男，1959年生，教授，博士生导师，主要研究方向为模式识别、网络管理、信息检索、基于内容的信息安全等.主持多项“863”计划项目和国家自然科学基金项目，获省部级奖励多项，发表学术论文上百篇，获授权专利5项.

更新日期/Last Update: 2012-05-07
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