A Probabilistic Model to Determine the Coherence of Texts in Interactive Question Answering Systems
Evaluation plays an important role in interactive question answering systems like many computational linguistics fields. The coherence between the questions and the answers exchanged between the user and the system is one of the important criteria in evaluating these systems. In this paper, a new ap...
Main Authors: | , |
---|---|
Format: | Article |
Language: | fas |
Published: |
Iranian Research Institute for Information and Technology
2018-09-01
|
Series: | Iranian Journal of Information Processing & Management |
Subjects: | |
Online Access: | http://jipm.irandoc.ac.ir/browse.php?a_code=A-10-3789-1&slc_lang=en&sid=1 |
id |
doaj-44c94253badb486e90953fa15700323e |
---|---|
record_format |
Article |
spelling |
doaj-44c94253badb486e90953fa15700323e2020-11-25T00:48:18ZfasIranian Research Institute for Information and TechnologyIranian Journal of Information Processing & Management2251-82232251-82312018-09-0133417371760A Probabilistic Model to Determine the Coherence of Texts in Interactive Question Answering SystemsMohammad Mehdi Hosseini0Morteza Zahedi1 Department of Computer Engineering; Shahrood University of Technology Department of Computer Engineering; Shahrood University of Technology Evaluation plays an important role in interactive question answering systems like many computational linguistics fields. The coherence between the questions and the answers exchanged between the user and the system is one of the important criteria in evaluating these systems. In this paper, a new approach to determine the degree of coherence of generated text by the IQA systems is presented. The proposed model is a probabilistic model in which for feature extraction, the similarity between different N-grams is derived based on four defined criteria. Then using a prediction of the best density function among the 18 functions considered for each feature, a model for determining the coherence is selected. The results of implementation on two databases provided by several interactive question answering systems indicate that the proposed probabilistic model is highly adapted and its accuracy in determining the degree of coherence in the conversation text has been made. The Kolmogorov-Smirnov, Anderson, Darling and Cramer van Meys trials were used to matching or non-matching probability density function. According to the presented results, the probability density factor with the least error was the best performance in determining the coherence of each conversation.http://jipm.irandoc.ac.ir/browse.php?a_code=A-10-3789-1&slc_lang=en&sid=1Matematical ModelingCoherence of TextIntearctive Question Answering Systems (IQAs)N-gramStatistical Similarity |
collection |
DOAJ |
language |
fas |
format |
Article |
sources |
DOAJ |
author |
Mohammad Mehdi Hosseini Morteza Zahedi |
spellingShingle |
Mohammad Mehdi Hosseini Morteza Zahedi A Probabilistic Model to Determine the Coherence of Texts in Interactive Question Answering Systems Iranian Journal of Information Processing & Management Matematical Modeling Coherence of Text Intearctive Question Answering Systems (IQAs) N-gram Statistical Similarity |
author_facet |
Mohammad Mehdi Hosseini Morteza Zahedi |
author_sort |
Mohammad Mehdi Hosseini |
title |
A Probabilistic Model to Determine the Coherence of Texts in Interactive Question Answering Systems |
title_short |
A Probabilistic Model to Determine the Coherence of Texts in Interactive Question Answering Systems |
title_full |
A Probabilistic Model to Determine the Coherence of Texts in Interactive Question Answering Systems |
title_fullStr |
A Probabilistic Model to Determine the Coherence of Texts in Interactive Question Answering Systems |
title_full_unstemmed |
A Probabilistic Model to Determine the Coherence of Texts in Interactive Question Answering Systems |
title_sort |
probabilistic model to determine the coherence of texts in interactive question answering systems |
publisher |
Iranian Research Institute for Information and Technology |
series |
Iranian Journal of Information Processing & Management |
issn |
2251-8223 2251-8231 |
publishDate |
2018-09-01 |
description |
Evaluation plays an important role in interactive question answering systems like many computational linguistics fields. The coherence between the questions and the answers exchanged between the user and the system is one of the important criteria in evaluating these systems. In this paper, a new approach to determine the degree of coherence of generated text by the IQA systems is presented. The proposed model is a probabilistic model in which for feature extraction, the similarity between different N-grams is derived based on four defined criteria. Then using a prediction of the best density function among the 18 functions considered for each feature, a model for determining the coherence is selected. The results of implementation on two databases provided by several interactive question answering systems indicate that the proposed probabilistic model is highly adapted and its accuracy in determining the degree of coherence in the conversation text has been made. The Kolmogorov-Smirnov, Anderson, Darling and Cramer van Meys trials were used to matching or non-matching probability density function. According to the presented results, the probability density factor with the least error was the best performance in determining the coherence of each conversation. |
topic |
Matematical Modeling Coherence of Text Intearctive Question Answering Systems (IQAs) N-gram Statistical Similarity |
url |
http://jipm.irandoc.ac.ir/browse.php?a_code=A-10-3789-1&slc_lang=en&sid=1 |
work_keys_str_mv |
AT mohammadmehdihosseini aprobabilisticmodeltodeterminethecoherenceoftextsininteractivequestionansweringsystems AT mortezazahedi aprobabilisticmodeltodeterminethecoherenceoftextsininteractivequestionansweringsystems AT mohammadmehdihosseini probabilisticmodeltodeterminethecoherenceoftextsininteractivequestionansweringsystems AT mortezazahedi probabilisticmodeltodeterminethecoherenceoftextsininteractivequestionansweringsystems |
_version_ |
1725256731146059776 |