Design Of Question Answering System Research Articles

Question Answering Systems: A Systematic Literature Review

Question answering systems (QAS) are developed to answer questions presented in natural language by extracting the answer. The development of QAS is aimed at making the Web more suited to human use by eliminating the need to sift through a lot of search results manually to determine the correct answer to a question. Accordingly, the aim of this study was to provide an overview of the current state of QAS research. It also aimed at highlighting the key limitations and gaps in the existing body of knowledge relating to QAS. Furthermore, it intended to identify the most effective methods utilized in the design of QAS. The systematic review of literature research method was selected as the most appropriate methodology for studying the research topic. This method differs from the conventional literature review as it is more comprehensive and objective. Based on the findings, QAS is a highly active area of research, with scholars taking diverse approaches in the development of their systems. Some of the limitations observed in these studies encompass the focused nature of current QAS, weaknesses associated with models that are used as building blocks for QAS, the need for standard datasets and question formats hence limiting the applicability of the QAS in practical settings, and the failure of researchers to examine their QAS solutions comprehensively. The most effective methods for designing QAS include focusing on syntax and context, utilizing word encoding and knowledge systems, leveraging deep learning, and using elements such as machine learning and artificial intelligence. Going forward, modular designs ought to be encouraged to foster collaboration in the creation of QAS.

基于知识库的智能客服机器人问答系统设计

基于知识库的智能客服机器人问答系统设计

Exploring the learning mechanism of web‐based question‐answering systems and their design

AbstractIn recent years, a number of models concerning question‐answering (QA) systems have been put forward. But many of them stress technology and neglect the research of QA itself. In this paper, we analyse the essence of QA and discuss the relationship between technology and QA. On that basis, we propose that when designing web‐based QA systems, more attention should be paid to the learning mechanism involved in the QA process than to technology. Some new ideas on the design of QA systems are also put forward in order to promote the rapid development of web‐based QA systems.

Formal methods in the design of question-answering systems

This paper contributes to the discussion whether and how predicate calculus should be used as a deep structure in question-answering programs. The first part of the paper stresses that there are several possible ways of using predicate calculus, and argues that predicate calculus has significant advantages above competing deep structures if the way of using it is carefully selected. The second half gives hints on how various natural-language constructions can be encoded in a consistent way, and how axion sets that define these encodings can be written and debugged.