基于启发式算法的复杂问题多领域知识图谱搜索

Jeongbin Kim, Jiyoon Kim, Hyeonseong Jo, Jason J. Jung, David Camacho
{"title":"基于启发式算法的复杂问题多领域知识图谱搜索","authors":"Jeongbin Kim, Jiyoon Kim, Hyeonseong Jo, Jason J. Jung, David Camacho","doi":"10.1109/iiai-aai53430.2021.00080","DOIUrl":null,"url":null,"abstract":"Question answering (QA) system is widely used because it finds the information that users want. Users can ask a variety of questions to the QA system, and the type of question is divided into a simple question and a complex question. A simple question is one query with one question while a complex question is one query with two or more questions. Although many studies have greatly improved the ability of the QA system to answer simple questions, answering complex questions remains a difficult problem. To solve the problem, we use the information from multiple domains and propose a method to quickly retrieve information from many data through a heuristic algorithm. For experiments, we use the movie, person, and country domain data as a knowledge base for the QA system, which is able to help solve the complex question. Compared to the widely used graph search algorithm Breadth-First Search (BFS) and Depth-First Search (DFS), the proposed method reduces the search time by 62% and 44% for finding the answers, respectively.","PeriodicalId":414070,"journal":{"name":"2021 10th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multiple Domains Knowledge Graph Search via Heuristic Algorithm for Answering Complex Questions\",\"authors\":\"Jeongbin Kim, Jiyoon Kim, Hyeonseong Jo, Jason J. Jung, David Camacho\",\"doi\":\"10.1109/iiai-aai53430.2021.00080\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Question answering (QA) system is widely used because it finds the information that users want. Users can ask a variety of questions to the QA system, and the type of question is divided into a simple question and a complex question. A simple question is one query with one question while a complex question is one query with two or more questions. Although many studies have greatly improved the ability of the QA system to answer simple questions, answering complex questions remains a difficult problem. To solve the problem, we use the information from multiple domains and propose a method to quickly retrieve information from many data through a heuristic algorithm. For experiments, we use the movie, person, and country domain data as a knowledge base for the QA system, which is able to help solve the complex question. Compared to the widely used graph search algorithm Breadth-First Search (BFS) and Depth-First Search (DFS), the proposed method reduces the search time by 62% and 44% for finding the answers, respectively.\",\"PeriodicalId\":414070,\"journal\":{\"name\":\"2021 10th International Congress on Advanced Applied Informatics (IIAI-AAI)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 10th International Congress on Advanced Applied Informatics (IIAI-AAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/iiai-aai53430.2021.00080\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 10th International Congress on Advanced Applied Informatics (IIAI-AAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iiai-aai53430.2021.00080","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

问答系统因为能够找到用户想要的信息而得到了广泛的应用。用户可以向QA系统提出各种各样的问题,问题的类型分为简单问题和复杂问题。简单问题是一个带有一个问题的查询,而复杂问题是一个带有两个或更多问题的查询。尽管许多研究已经大大提高了QA系统回答简单问题的能力,但回答复杂问题仍然是一个难题。为了解决这一问题,我们利用多领域的信息,提出了一种通过启发式算法从大量数据中快速检索信息的方法。在实验中,我们使用电影、人物和国家领域的数据作为QA系统的知识库,能够帮助解决复杂的问题。与目前广泛使用的图搜索算法广度优先搜索(BFS)和深度优先搜索(DFS)相比,该方法的搜索时间分别缩短了62%和44%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Multiple Domains Knowledge Graph Search via Heuristic Algorithm for Answering Complex Questions
Question answering (QA) system is widely used because it finds the information that users want. Users can ask a variety of questions to the QA system, and the type of question is divided into a simple question and a complex question. A simple question is one query with one question while a complex question is one query with two or more questions. Although many studies have greatly improved the ability of the QA system to answer simple questions, answering complex questions remains a difficult problem. To solve the problem, we use the information from multiple domains and propose a method to quickly retrieve information from many data through a heuristic algorithm. For experiments, we use the movie, person, and country domain data as a knowledge base for the QA system, which is able to help solve the complex question. Compared to the widely used graph search algorithm Breadth-First Search (BFS) and Depth-First Search (DFS), the proposed method reduces the search time by 62% and 44% for finding the answers, respectively.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
An analysis of preferences of convention attendees in the time of Covid-19 pandemic Visual Effects for Real Time Ocean Water Rendering Analysis of commands of Telnet logs illegally connected to IoT devices Design, modeling and parameters identification of rotary-type double inverted pendulum An Improved NSGA-II for Service Provider Composition in Knowledge-Intensive Crowdsourcing
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1