Toward Automatic Answers in User-Interactive Question Answering Systems

2011 ◽  
Vol 3 (4) ◽  
pp. 52-66 ◽  
Author(s):  
Tianyong Hao ◽  
Feifei Xu ◽  
Jingsheng Lei ◽  
Liu Wenyin ◽  
Qing Li
Keyword(s):  
Pattern Matching ◽  
Similar Pattern ◽  
Question Answering ◽  
Semantic Representation ◽  
Pattern Generation ◽  
Interactive Systems ◽  
Question Answering System ◽  
Semantic Annotations ◽  
Question Answering Systems ◽  
Interactive Question

A strategy of automatic answer retrieval for repeated or similar questions in user-interactive systems by employing semantic question patterns is proposed in this paper. The used semantic question pattern is a generalized representation of a group of questions with both similar structure and relevant semantics. Specifically, it consists of semantic annotations (or constraints) for the variable components in the pattern and hence enhances the semantic representation and greatly reduces the ambiguity of a question instance when asked by a user using such pattern. The proposed method consists of four major steps: structure processing, similar pattern matching and filtering, automatic pattern generation, question similarity evaluation and answer retrieval. Preliminary experiments in a real question answering system show a precision of more than 90% of the method.

Toward Automatic Answers in User-Interactive Question Answering Systems

2013 ◽  
pp. 88-101
Author(s):  
Tianyong Hao ◽  
Feifei Xu ◽  
Jingsheng Lei ◽  
Liu Wenyin ◽  
Qing Li
Keyword(s):  
Pattern Matching ◽  
Similar Pattern ◽  
Question Answering ◽  
Semantic Representation ◽  
Pattern Generation ◽  
Interactive Systems ◽  
Question Answering System ◽  
Semantic Annotations ◽  
Question Answering Systems ◽  
Interactive Question

A strategy of automatic answer retrieval for repeated or similar questions in user-interactive systems by employing semantic question patterns is proposed in this paper. The used semantic question pattern is a generalized representation of a group of questions with both similar structure and relevant semantics. Specifically, it consists of semantic annotations (or constraints) for the variable components in the pattern and hence enhances the semantic representation and greatly reduces the ambiguity of a question instance when asked by a user using such pattern. The proposed method consists of four major steps: structure processing, similar pattern matching and filtering, automatic pattern generation, question similarity evaluation and answer retrieval. Preliminary experiments in a real question answering system show a precision of more than 90% of the method.

Ontology based Baysian network for clinical specialty supporting in interactive question answering systems

2017 ◽  
Vol 34 (7) ◽  
pp. 2435-2447
Author(s):  
Jui-Feng Yeh ◽  
Yu-Jui Huang ◽  
Kao-Pin Huang
Keyword(s):  
Natural Language ◽  
Question Answering ◽  
Clinical Specialty ◽  
Content Type ◽  
Question Answering System ◽  
Concept Space ◽  
Question Answering Systems ◽  
Decision Supporting ◽  
Interactive Question ◽  
Good Score

Purpose This study aims to provide an ontology based Baysian network for clinical specialty supporting. As a knowledge base, ontology plays an essential role in domain applications especially in expert systems. Interactive question answering systems are suitable for personal domain consulting and recommended for real-time usage. Clinical specialty supporting for dispatching patients can assist hospitals to locate desired treatment departments for individuals relevant to their syndromes and disease efficiently and effectively. By referring to interactive question answering systems, individuals can understand how to alleviate time and medical resource wasting according to recommendations from medical ontology-based systems. Design/methodology/approach This work presents an ontology based on clinical specialty supporting using an interactive question answering system to achieve this aim. The ontology incorporates close temporal associations between words in input query to represent word co-occurrence relationships in concept space. The patterns defined in lexicon chain mechanism are further extracted from the query words to infer related concepts for treatment departments to retrieve information. Findings The precision and recall rates are considered as the criteria for model optimization. Finally, the inference-based interactive question answering system using natural language interface is adopted for clinical specialty supporting, and indicates its superiority in information retrieval over traditional approaches. Originality/value From the observed experimental results, we find the proposed method is useful in practice especially in treatment department decision supporting using metrics precision and recall rates. The interactive interface using natural language dialogue attracts the users’ attention and obtains a good score in mean opinion score measure.

A π-Calculus-Based Complaint Model for a User-Interactive Question Answering System

2013 ◽  
Vol 756-759 ◽  
pp. 2178-2183
Author(s):  
Yan Cheng Li ◽  
Hua Duan ◽  
Qing Tian Zeng ◽  
Fa Ming Lu
Keyword(s):  
Question Answering ◽  
Formal Model ◽  
Formal Analysis ◽  
Special Significance ◽  
Question Answering System ◽  
Research Results ◽  
Question Answering Systems ◽  
Interactive Question ◽  
Π Calculus

User-interactive question answering systems are catching more and more attention, however users complaints arise within it from such problems as unfair compensation. This paper focuses on a π-calculus-based formal model for the complaint process of a user-interactive question answering system. The formal model is verified by employing MWB tools so as to demonstrate the deadlock-free and other properties. The research results are of special significance to the comprehensive formal analysis of the user-interactive question answering systems.

Questionnaires for eliciting evaluation data from users of interactive question answering systems

2009 ◽  
Vol 15 (1) ◽  
pp. 119-141 ◽  
Author(s):  
D. KELLY ◽  
P. B. KANTOR ◽  
E. L. MORSE ◽  
J. SCHOLTZ ◽  
Y. SUN
Keyword(s):  
Question Answering ◽  
Validity And Reliability ◽  
Evaluation Data ◽  
Evaluation Measures ◽  
Relevance Judgments ◽  
Question Answering Systems ◽  
Interactive Question ◽  
Initial Support ◽  
Nasa Tlx ◽  
And Task

AbstractEvaluating interactive question answering (QA) systems with real users can be challenging because traditional evaluation measures based on the relevance of items returned are difficult to employ since relevance judgments can be unstable in multi-user evaluations. The work reported in this paper evaluates, in distinguishing among a set of interactive QA systems, the effectiveness of three questionnaires: a Cognitive Workload Questionnaire (NASA TLX), and Task and System Questionnaires customized to a specific interactive QA application. These Questionnaires were evaluated with four systems, seven analysts, and eight scenarios during a 2-week workshop. Overall, results demonstrate that all three Questionnaires are effective at distinguishing among systems, with the Task Questionnaire being the most sensitive. Results also provide initial support for the validity and reliability of the Questionnaires.

scholarly journals BUILDING QUESTION ANSWERING SYSTEM BASED ON COMPUTING DOMAIN ONTOLOGY

2020 ◽  
Vol 38 (02) ◽  
Author(s):  
TẠ DUY CÔNG CHIẾN
Keyword(s):  
Language Processing ◽  
Digital Libraries ◽  
Question Answering ◽  
Domain Ontology ◽  
Text Documents ◽  
Question Answering System ◽  
Domain Specific ◽  
Sql Database ◽  
Question Answering Systems ◽  
Education Business

Question answering systems are applied to many different fields in recent years, such as education, business, and surveys. The purpose of these systems is to answer automatically the questions or queries of users about some problems. This paper introduces a question answering system is built based on a domain specific ontology. This ontology, which contains the data and the vocabularies related to the computing domain are built from text documents of the ACM Digital Libraries. Consequently, the system only answers the problems pertaining to the information technology domains such as database, network, machine learning, etc. We use the methodologies of Natural Language Processing and domain ontology to build this system. In order to increase performance, I use a graph database to store the computing ontology and apply no-SQL database for querying data of computing ontology.

scholarly journals A New Statistical Model for Evaluation Interactive Question Answering Systems Using Regression

2019 ◽  
Vol 16 (3) ◽  
pp. 48-37
Author(s):  
mohammad mehdi hosseini ◽  
Morteza zahedi ◽  
hamid Hassanpour ◽  
◽  
◽  
...  
Keyword(s):  
Statistical Model ◽  
Question Answering ◽  
Question Answering Systems ◽  
Interactive Question

scholarly journals User-centered evaluation of interactive question answering systems

2006 ◽  
Author(s):  
Diane Kelly ◽  
Paul B. Kantor ◽  
Emile L. Morse ◽  
Jean Scholtz ◽  
Ying Sun
Keyword(s):  
Question Answering ◽  
Question Answering Systems ◽  
Interactive Question ◽  
User Centered

scholarly journals Designing an interactive open-domain question answering system

2009 ◽  
Vol 15 (1) ◽  
pp. 73-95 ◽  
Author(s):  
S. QUARTERONI ◽  
S. MANANDHAR
Keyword(s):  
Web Search ◽  
Question Answering ◽  
Management Model ◽  
Open Domain ◽  
Wizard Of Oz ◽  
Question Answering System ◽  
Design And Implementation ◽  
Web Search Engine ◽  
Interactive Question

AbstractInteractive question answering (QA), where a dialogue interface enables follow-up and clarification questions, is a recent although long-advocated field of research. We report on the design and implementation of YourQA, our open-domain, interactive QA system. YourQA relies on a Web search engine to obtain answers to both fact-based and complex questions, such as descriptions and definitions. We describe the dialogue moves and management model making YourQA interactive, and discuss the architecture, implementation and evaluation of its chat-based dialogue interface. Our Wizard-of-Oz study and final evaluation results show how the designed architecture can effectively achieve open-domain, interactive QA.

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