Development research of highly accurate Question Answering system doing precise matching of meaning

语义精准匹配的高精度问答系统开发研究

基本信息

  • 批准号:
    16500085
  • 负责人:
  • 金额:
    $ 2.3万
  • 依托单位:
  • 依托单位国家:
    日本
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
  • 财政年份:
    2004
  • 资助国家:
    日本
  • 起止时间:
    2004 至 2006
  • 项目状态:
    已结题

项目摘要

We have developed Metis, a question-answering system that finds an answer by matching a question graph with the knowledge graphs. The question graph is obtained as a result of semantic analysis of a question sentence, the knowledge graphs are similarly analyzed from knowledge sentences retrieved from a database using keywords extracted from the question sentence. In retrieving such knowledge sentences, the system searches for and collects them using Lucene, a search engine, based on search keywords extracted from the question graph. To extract the answer, Metis calculates the degrees of similarity between the question and knowledge graphs to conduct precise matching. In this matching, the system calculates the degrees of similarity, which is the relative size of the similarity co-occurrence graph to the question graphs with respect to all combinations of nodes in the knowledge graph corresponding to those in the question graph. The system then chooses the knowledge graph with the highest degree of similarity and extracts from it the portion that corresponds to the given interrogative word. The system presents this portion as the answer. The evaluation experiment was done by using 100 quiz millionaire questions. The precision to obtain the correct answer within the first three answers was 74%. Moreover, it participated in the evaluation contest in NTCIR, and the precision was 18% in QAC which asked factoid question, the precision was 22% in CLQA which asked the reasons, the method and etc.
我们开发了Metis,一个问答系统,通过将问题图与知识图相匹配来找到答案。问题图是作为问题句子的语义分析的结果而获得的,知识图是类似地从使用从问题句子提取的关键字从数据库检索的知识句子中分析的。在检索这些知识句时,系统基于从问题图中提取的搜索关键字,使用搜索引擎Lucene搜索并收集它们。为了提取答案,Metis计算问题和知识图之间的相似度,以进行精确匹配。在该匹配中,系统计算相似度,相似度是相似同现图相对于与问题图中的节点相对应的知识图中的节点的所有组合与问题图的相对大小。然后,系统选择具有最高相似度的知识图,并从中提取与给定疑问词相对应的部分。系统将此部分显示为答案。评价实验采用100个百万富翁问题。在前三个答案中获得正确答案的准确率为74%。并参加了NTCIR的测评竞赛,在QAC中提出的事实性问题的正确率为18%,在CLQA中提出的原因、方法等问题的正确率为22%。

项目成果

期刊论文数量(52)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
QA System Metis Based on Semantic Graph Matching
基于语义图匹配的问答系统Metis
Summary generation centered on important words
以重要单词为中心的摘要生成
意味解析を踏まえた自動要約システムABISYS
ABISYS,基于语义分析的自动摘要系统
Research of Anaphoric analysis based on Semantic analysis
基于语义分析的照应分析研究
Determination of voice, tense, aspect and moodin the Japanese semantic analysis system SAGE
日语语义分析系统SAGE中的语音、时态、体态、语气的判定
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HARADA Minoru其他文献

HARADA Minoru的其他文献

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{{ truncateString('HARADA Minoru', 18)}}的其他基金

Semantic and Contextual Analysis using Common knowledge from Japanese Articles
使用日语文章中的常识进行语义和上下文分析
  • 批准号:
    13680461
  • 财政年份:
    2001
  • 资助金额:
    $ 2.3万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
A Research of machine learning of object oriented analysis knowledge by induvtive reasoning
归纳推理面向对象分析知识的机器学习研究
  • 批准号:
    09680377
  • 财政年份:
    1997
  • 资助金额:
    $ 2.3万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
A Research of Reverse Engineering Tool which generates a non-procedural specification from COBOL programs
从COBOL程序生成非过程规范的逆向工程工具的研究
  • 批准号:
    07680434
  • 财政年份:
    1995
  • 资助金额:
    $ 2.3万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)

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  • 财政年份:
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