Modification of an automatic method for extracting causal relationships based on templates and a Bayesian classifier
Objective. The aim of the study is to modify the automatic method for extracting cause-and-effect relationships.Method. The study is based on the original method of Antonie Sorgente with its subsequent modification.Result. A method for extracting cause-and-effect relationships is proposed. The metho...
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| Format: | Article |
| Language: | Russian |
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Dagestan State Technical University
2025-04-01
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| Series: | Вестник Дагестанского государственного технического университета: Технические науки |
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| Online Access: | https://vestnik.dgtu.ru/jour/article/view/1710 |
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| _version_ | 1849250198767796224 |
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| author | Н. В. Shtanchaev Z. T. Mugutdinov |
| author_facet | Н. В. Shtanchaev Z. T. Mugutdinov |
| author_sort | Н. В. Shtanchaev |
| collection | DOAJ |
| description | Objective. The aim of the study is to modify the automatic method for extracting cause-and-effect relationships.Method. The study is based on the original method of Antonie Sorgente with its subsequent modification.Result. A method for extracting cause-and-effect relationships is proposed. The method involves the combined use of statistical data and machine methods. The original method was modified by translating the method to modern libraries such as NLTK and Spacy. The rules formed by the author were reworked and added to the Dependency Matcher module of the Spacy library. The number of keywords for each rule was increased. The method also takes into account synonyms, calculates Bayesian statistics and smooths Laplace for zero probabilities. Based on the difference in data with and without PSS, a multiplier coefficient was introduced to compensate for the skew of classes in the data.Conclusion. The developed method was tested on the original data of the original method and showed improved metrics relative to the original method on training and test data. |
| format | Article |
| id | doaj-art-daa5e5d2e2504bc4a4cbca44f2c7c3f7 |
| institution | Kabale University |
| issn | 2073-6185 2542-095X |
| language | Russian |
| publishDate | 2025-04-01 |
| publisher | Dagestan State Technical University |
| record_format | Article |
| series | Вестник Дагестанского государственного технического университета: Технические науки |
| spelling | doaj-art-daa5e5d2e2504bc4a4cbca44f2c7c3f72025-08-20T03:57:21ZrusDagestan State Technical UniversityВестник Дагестанского государственного технического университета: Технические науки2073-61852542-095X2025-04-0152116217210.21822/2073-6185-2025-52-1-162-172966Modification of an automatic method for extracting causal relationships based on templates and a Bayesian classifierН. В. Shtanchaev0Z. T. Mugutdinov1Daghestan State Technical UniversityOOO "Salavatsteklo Caspian"Objective. The aim of the study is to modify the automatic method for extracting cause-and-effect relationships.Method. The study is based on the original method of Antonie Sorgente with its subsequent modification.Result. A method for extracting cause-and-effect relationships is proposed. The method involves the combined use of statistical data and machine methods. The original method was modified by translating the method to modern libraries such as NLTK and Spacy. The rules formed by the author were reworked and added to the Dependency Matcher module of the Spacy library. The number of keywords for each rule was increased. The method also takes into account synonyms, calculates Bayesian statistics and smooths Laplace for zero probabilities. Based on the difference in data with and without PSS, a multiplier coefficient was introduced to compensate for the skew of classes in the data.Conclusion. The developed method was tested on the original data of the original method and showed improved metrics relative to the original method on training and test data.https://vestnik.dgtu.ru/jour/article/view/1710cause and effectnatural language processingnltkspacycausalitycauseeffectstatic methodsnon-static methodsmachine methods |
| spellingShingle | Н. В. Shtanchaev Z. T. Mugutdinov Modification of an automatic method for extracting causal relationships based on templates and a Bayesian classifier Вестник Дагестанского государственного технического университета: Технические науки cause and effect natural language processing nltk spacy causality cause effect static methods non-static methods machine methods |
| title | Modification of an automatic method for extracting causal relationships based on templates and a Bayesian classifier |
| title_full | Modification of an automatic method for extracting causal relationships based on templates and a Bayesian classifier |
| title_fullStr | Modification of an automatic method for extracting causal relationships based on templates and a Bayesian classifier |
| title_full_unstemmed | Modification of an automatic method for extracting causal relationships based on templates and a Bayesian classifier |
| title_short | Modification of an automatic method for extracting causal relationships based on templates and a Bayesian classifier |
| title_sort | modification of an automatic method for extracting causal relationships based on templates and a bayesian classifier |
| topic | cause and effect natural language processing nltk spacy causality cause effect static methods non-static methods machine methods |
| url | https://vestnik.dgtu.ru/jour/article/view/1710 |
| work_keys_str_mv | AT nvshtanchaev modificationofanautomaticmethodforextractingcausalrelationshipsbasedontemplatesandabayesianclassifier AT ztmugutdinov modificationofanautomaticmethodforextractingcausalrelationshipsbasedontemplatesandabayesianclassifier |