检索结果-南通市图书馆

text reasoning Chain Extraction for Multi-Hop Question Answering

Tsinghua Science and Technology 2024年第4期29卷 959-970页

作者： Pengming Wang Zijiang Zhu Qing Chen Weihuang Dai School of Data Science and Artificial Intelligence Wenzhou University of TechnologyWenzhou 325035China School of Computer Science and also with Institute of Intelligent Information ProcessingSouth China Business CollegeGuangdong University of Foreign StudiesGuangzhou 510545China School of Psychology Jiangxi Normal UniversityNanchang 330022China also with School of Science East China Jiaotong UniversityNanchang 330013China Institute of Intelligent Information Processing South China Business CollegeGuangdong University of Foreign StudiesGuangzhou 510545China

With the advent of the information age, it will be more troublesome to search for a lot of relevant knowledge to find the information you need. text reasoning is a very basic and important part of multi-hop question and answer tasks. This paper aims to study the integrity, uniformity, and speed of computational intelligence inference data capabilities. That is why multi-hop reasoning came into being, but it is still in its infancy, that is, it is far from enough to conduct multi-hop question and answer questions, such as search breadth, process complexity, response speed, comprehensiveness of information, etc. This paper makes a text comparison between traditional information retrieval and computational intelligence through corpus relevancy and other computing methods. The study finds that in the face of multi-hop question and answer reasoning, the reasoning data that traditional retrieval methods lagged behind in intelligence are about 35% worse. It shows that computational intelligence would be more complete, unified, and faster than traditional retrieval methods. This paper also introduces the relevant points of text reasoning and describes the process of the multi-hop question answering system, as well as the subsequent discussions and expectations.

关键词： intelligent computing multi-hop quiz text reasoning document retrieval text complex network

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