A Study for Knowledge ExtractionAid System from Web Text

网络文本知识提取辅助系统的研究

• 批准号: 17200007
• 负责人: NAKAGAWA Hiroshi
• 金额: $ 27.79万
• 依托单位: The University of Tokyo
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (A)
• 财政年份: 2005
• 资助国家: 日本
• 起止时间: 2005 至 2007
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-17200007/
• 关键词: WWW; Knowledge; Text; Mining; Usage Retrieval; People Name Search; Terminology Extraction; Machine Learning; 検索; テキストマイニング; 半構造テキスト; ブログ; Trie; n-gram; 情報検索; インデキシング; 自然言語処理; 用例

We aimed at a system that extracts texts or part of texts including knowledge which various users are interested in from huge amount of Web pages in this research. We developed the following systems for this purpose.(1) A system which extracts terms that characterize a search engine result web pages using the term extraction system "Gensen Web" which we have already developed.(2) A system which extracts definition of terms which we extract by the system of (1) and relations among these terms. To accomplish this task, we utilize the usage consultation system via Web search engine called "Kiwi."(3) In order to make more efficient system of (2), we employed a suffix array technology and use the web pages crawled in advance. We named the system as "UT-Kiwi" and made it publically available from the Internet.(4) To enhance the above described systems, we developed a people name search engine named "Nayose." When we search pages for given people name, we get pages indicating distinct person even though they have the same name. Our system clusters those web pages according to the real person.(5) Aiming at more innovative knowledge extraction, we also studied new machine learning algorithms based on non-parametric Bayes theory.(6) Utilize web page in English more, we developed the Sakumon system which is an assisting system for English cloze test using English web pages.

本研究的目标是从海量的Web页面中抽取文本或部分文本，其中包含各种用户感兴趣的知识。为此，我们开发了以下系统。(1)使用我们已经开发的术语提取系统Gensen Web来提取表征搜索引擎结果网页的术语的系统。(2)通过(1)的系统提取术语的定义以及这些术语之间的关系的系统。为了完成这一任务，我们利用了通过Web搜索引擎的使用咨询系统--猕猴桃。(3)为了使(2)的系统更高效，我们采用了后缀数组技术，并使用了预先抓取的网页。我们将该系统命名为“UT-Kiwi”，并将其从互联网上公开提供。(4)为了增强上述系统，我们开发了一个名为“Nayose”的人名搜索引擎。当我们在页面上搜索给定的人名时，我们得到的页面指示不同的人，即使他们的名字相同。针对更具创新性的知识提取，研究了基于非参数贝叶斯理论的机器学习算法。(6)进一步利用英文网页，开发了英语完形填空辅助系统Sakumon系统。

项目成果

用例検索システムKiwiの知識テキストマイニングツールへの拡張

将示例搜索系统 Kiwi 扩展为知识文本挖掘工具

• 发表时间: 2006
• 期刊: 言語処理学会年次大会 第12回
• 作者: 藤本宏涼;国安結;中川裕志;吉田稔;清田陽司
• 通讯作者: 清田陽司

A Multilingual Usage Consultation Tool based on Internet Searching ---More than search engine, Less than QA

基于互联网搜索的多语言使用咨询工具——不止于搜索引擎，低于QA

• 发表时间: 2005
• 期刊: The Proceedings of 14th International World Wide Web Conference WWW2005
• 作者: Kumiko Tanaka-Ishii;Hiroshi Nakagawa
• 通讯作者: Hiroshi Nakagawa

Cross-Lingual Concern Analysisi from Multiingual Weblog Articles

多语言博客文章中的跨语言关注分析

• 发表时间: 2007
• 作者: Tomohiro Fukuhara;Takehito Utsuro;Hiroshi Nakagawa
• 通讯作者: Hiroshi Nakagawa

Understanding Sentiment of People from News Articles: Temporal Sentiment Analysis of Social Events

• 发表时间: 2007
• 作者: T. Fukuhara;Hiroshi Nakagawa;T. Nishida

Application of Variational Bayse to Dirichlet Process Unigram Mixture Model

变分贝叶斯在狄利克雷过程一元混合模型中的应用

• 发表时间: 2007
• 期刊: IPSJ Transaction 48
• 作者: Issei Sato;Hiroshi Nakagawa
• 通讯作者: Hiroshi Nakagawa