Senem Kumova Metın, Bahar Karaoğlan, Tarık Kışla et al. · Pamukkale University Journal of Engineering Sciences · 2021
In this paper, we address the problem of uncertainty management in identification of paraphrase sentence pairs. Paraphrase sentences are simply sets/pairs of sentences that express the same facts and/or opinions using different words or order of words. We propose the use of certainty factor (CF) model in paraphrase detection. A set of succeeding paraphrase detection features (generic and distance based features) is built by filtering and this set is used as evidences in CF model. The CF model is evaluated by F1 and accuracy measures on Microsoft Research Paraphrase corpus. The results are compared to the well-known Bayesian reasoning. The experimental results showed that CF model is an alternating paraphrase detection method to Bayes model. Bu makalede, eanlatml cmle iftlerinin belirlenmesindeki belirsizlik problemi zerinde durulmutur. Eanlatm cmleleri basite ayn olay ve/veya fikri farkl szck veya szcklerin farkl dizilileri ile ifade eden cmle iftleri/kmeleridir. almada eanlatm tespitinde eminlik faktr (EF) modelinin kullanlmas nerilmitir. EF modelinde kullanlmak zere filtreleme yntemi ile eanlatm tespitinde baarl olan znitelikler (jenerik ve uzaklk tabanl znitelikler) belirlenmi ve bu znitelikler kmesi EF modelinde deliller olarak kullanlmtr. EF modeli Microsoft Eanlatm derlemi zerinde F1 ve doruluk lekleri
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Katira Soleymanzadeh, Tarık Kışla, Bahar Karaoğlan et al. · SHILAP Revista de lepidopterología · 2021
In this paper, we address the problem of uncertainty management in identification of paraphrase sentence pairs. Paraphrase sentences are simply sets/pairs of sentences that express the same facts and/or opinions using different words or order of words. We propose the use of certainty factor (CF) model in paraphrase detection. A set of succeeding paraphrase detection features (generic and distance based features) is built by filtering and this set is used as evidences in CF model. The CF model is evaluated by F1 and accuracy measures on Microsoft Research Paraphrase corpus. The results are compared to the well-known Bayesian reasoning. The experimental results showed that CF model is an alternating paraphrase detection method to Bayes model.
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Rong Wang · 2004
In this paper, the relations and differences between certainty factor model and Bayesian Network are researched. Firstly, the limitation of the theoretical basis of certainty factor model is discussed; it is proved that the certainty factor model implies a conditional independence hypothesis same as the simple Bayesian model implies. Then, some functions of Bayesian Network, which correspond to certainty factor model, are explored. The concepts, analysis approach, and computing formula of condition's influence degree and effect direction to the inference conclusion in Bayesian network are presented, and it is also proved that the equivalence of the probabilistic inference between the Noisy-OR model and certainty factor model. Finally, the superiority of Bayesian network to certainty factor model is discussed in the aspects of representation, inference, and acquire of the knowledge. Our conclusion is that the Bayesian network not only has the main function of the certainty factor model, but also can break through some limitation of this model, so the Bayesian network can be a main trend probabilistic model in intelligent information process instead of the certainty factor model eventually.
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Linda van der Gaag · Utrecht University Repository (Utrecht University) · 1990
Since its introduction in the 1970s, the certainty factor model has enjoyed widespread use in rule-based expert systems. Many present-day, commercially available expert system shells offer the model for modelling and reasoning with uncertain information.
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Yanfeng Jin, Yongping Wang, Keming Geng et al. · Lecture notes in electrical engineering · 2012
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Bob Goedhart, G. Noij · Expert Systems with Applications · 1992
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Luo Mingyu · 2010
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Exalthya Sera, Fadilah Fadilah, Bahar Bahar · Progresif Jurnal Ilmiah Komputer · 2025
Limited access to veterinary health services, farmers’ lack of knowledge, and the high cost and time required for consultations are major obstacles in handling cattle diseases, especially in remote areas. These issues often lead to delays in diagnosis and treatment, resulting in significant economic losses. This study proposes the development of a computer-based expert system using the Certainty Factor method as a solution to assist farmers in independently diagnosing cattle diseases. The system is equipped with its main feature, a diagnosis process, as well as a chat feature for direct consultation with veterinarians as a novelty element. Testing was conducted on 19 test data by comparing the system’s diagnostic results with those of experts, showing a match rate of 84.21% and 15.79% mismatch due to symptom similarities and differences in severity interpretation. The results demonstrate that the system has fairly good accuracy and is suitable for use as an early diagnostic tool, which is expected to accelerate disease handling and reduce farmers’ economic losses. Keywords: Expert System; Certainty Factor; Cattle Disease Diagnosis; Veterinary Consultation Chat. Abstrak Keterbatasan akses layanan kesehatan hewan, minimnya pengetahuan peternak, serta biaya dan waktu yang tinggi untuk konsultasi menjadi hambatan dalam penanganan penyakit sapi, khususnya di daerah terpencil. Permasalahan ini kerap mengakibatkan keterlambatan diagnosis dan penanganan, sehingga menimbulkan kerugian ekonomi yang signifikan. Penelitian ini mengusulkan pengembangan sistem pakar berbasis komputer menggunakan metode Certainty Factor sebagai solusi untuk membantu peternak mendiagnosis penyakit sapi secara mandiri. Sistem ini dilengkapi dengan fitur utamanya proses diagnosis, serta fitur chat untuk konsultasi langsung dengan dokter hewan sebagai unsur kebaruan. Pengujian dilakukan pada 19 data uji dengan membandingkan hasil diagnosis sistem dan pakar, menunjukkan tingkat kesesuaian sebesar 84,21% dan 15,79% tidak sesuai akibat kemiripan gejala serta perbedaan interpretasi tingkat keparahan. Hasil ini membuktikan bahwa sistem memiliki akurasi yang cukup baik dan layak digunakan sebagai alat bantu diagnosis awal, yang diharapkan dapat mempercepat penanganan penyakit dan mengurangi kerugian ekonomi peternak. Kata kunci : Sistem Pakar; Certainty Factor; Diagnosis Penyakit Sapi; Chat Konsultasi Dokter Hewan .
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Xiong Cai · 2014
Argumentation is a kind of interaction between agents for resolving differences in speech. Due to the limitation of knowledge, arguments and its inner statements are usually uncertain, and therefore it is necessary to consider uncertain information processing when modeling the process of argumentation. This paper proposes an argumentation model based on the theory of certainty-factor, in which an argument is expressed as a defeasible rule with several premises but only one conclusion, and the process of argumentation is described as a dialogue tree. In order to do uncertain reasoning, the uncertainty of argument's premise and the strength of the attack that one argument makes against another are assigned with certainty-factors. Next, the algorithms of argument evaluation are provided to compute the credibility of statements. Using the algorithms the set of acceptable arguments can be determined by the credibility threshold and the result of argumentation can be obtained. Finally, an example is given to illustrate the validity of the method. The algorithms are based on numerical computation where the set of acceptable arguments is unique under a given credibility threshold, and can overcome the shortage of extension semantics of Dung's abstract argumentation framework.
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Izzu Zantya Fawwas, Casi Setianingsih, Fussy Mentari Dirgantara et al. · BIO Web of Conferences · 2023
In lecture activities, students are required to master several courses that have been determined based on their respective majors. In the learning process, students often have difficulty understanding lecture material. One factor is the mismatch between how students learn and the type of learning style of each student. It is important for each student to know their respective learning styles so that in the learning process can understand the material to the fullest. One way to find out the type of student learning style is with VARK modalities (Visual, Auditory, Read/Write, and Kinaesthetic). The VARK model classifies learning style types into four types. Everyone must have all four types of learning styles, but there must be one of the most dominant. By knowing the type of learning style, students can determine how to learn according to the type of learning style. This recommendation system is implemented using Certainty Factor algorithms involving the expertise of a psychologist in it, this system is built in the website platform. The system achieves an accuracy of 94.52%, so it is good enough to provide recommendations on how to learn properly for users.
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Izzu Zantya Fawwas, Casi Setianingsih, Fussy Mentari Dirgantara et al. · Springer Link (Chiba Institute of Technology) · 2023
\nIn lecture activities, students are required to master several courses that have been determined based on their respective majors. In the learning process, students often have difficulty understanding lecture material. One factor is the mismatch between how students learn and the type of learning style of each student. It is important for each student to know their respective learning styles so that in the learning process can understand the material to the fullest. One way to find out the type of student learning style is with VARK modalities (Visual, Auditory, Read/Write, and Kinaesthetic). The VARK model classifies learning style types into four types. Everyone must have all four types of learning styles, but there must be one of the most dominant. By knowing the type of learning style, students can determine how to learn according to the type of learning style. This recommendation system is implemented using Certainty Factor algorithms involving the expertise of a psychologist in it, this system is built in the website platform. The system achieves an accuracy of 94.52%, so it is good enough to provide recommendations on how to learn properly for users.\n
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Xudong Luo, Chengqi Zhang, Yuhui Qiu · 1997
In this paper, we prove that the EMYCIN formula for the sequential propagation can be derived strictly from the definition of the certainty factor according to probability theory. Some researchers think that this combination formula is inconsistent with the definition of certainty factor in the sense of probability theory. This was not correct. Moreover, under the condition that there exists no need for prior probabilities to be supplied with values, we reformulate the parallel propagation from the definition of the certainty factor according to probability theory. Therefore, the paper normalizes the relationship between the definition of the certainty factor and combination formulae for sequential and parallel propagations. In conclusion, this paper demonstrated that the certainty factor model can be built on the foundation of probability theory. Keywords: Uncertainty, Expert System, Prior Probability, Extension Conditional Probability, Certainty Factor, Ternary Rule Strength. 1 Int...
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Khôi, Lê Hải · Journal of Computer Science and Cybernetics (Vietnam Academy of Science and Technology) · 2012
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Guang Yang, XU Peihua, Chen Cao et al. · 2019
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Fei WANG, Liwei ZHOU, Tiesheng YAN et al. · SHILAP Revista de lepidopterología · 2025
The gradient boosting model (GBM) has demonstrated strong predictive performance in landslide susceptibility assessment; however, the complexity of factors limits its stability and accuracy. To improve the model’s accuracy in susceptibility assessments from the input level, this study explored the optimization effect of the certainty factor (CF) coupling method on the GBM. using Yongjia County in Zhejiang Province as a case study, 10 evaluation factors were selected based on Spearman correlation coefficient and Shapley value. The CF coupling method was applied to optimize four GBM models: Ada, Gentle, Logit, and RUS, which were then compared. The results show that the factors most significantly affecting landslides in the study area, in descending order, are: elevation, normalized vegetation index, roads, slope, water systems, land type, sediment transport index, vegetation type, lithology, and rainfall. Optimization using the CF coupling method improved the Kappa coefficient of GBM models by 0.04 to 0.14. ROC (receiver operating characteristic) curve validation showed that, except for the adaptive boosting model with a smaller performance increase, the AUC (area under curve) values of the other models increased by 1% to 7%, with the CF-Logit Boosting model achieving the highest accuracy. The optimized models demonstrated better distinction between very low and very high susceptibility areas, indicating that the CF coupling method can enhance both the accuracy and stability of the models. The GBM models optimized by CF coupling method could provides a theoretical basis for reducing data complexity and improving the accuracy of landslide susceptibility assessments.
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NTUR (臺灣機構典藏) · 2011
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Fillahi Zaki Alhaqi, Wahyu Triono, Agust Isa Martinus · INTI TALAFA · 2024
To support the learning process, one must know their suitable learning style. Many students are already familiar with the concept of learning styles but still struggle to determine their own compatible style. Additionally, the absence of teachers teaching about learning styles contributes to the ineffectiveness of the learning process. Therefore, a system is needed to identify a student's learning style that matches their habits. Based on the existing issues, a student learning style identification system has been created as an alternative to assist students in identifying their compatible learning style. It implements the forward chaining method to record student responses and generate user Certainty Factors (CF) from those responses. This is followed by the Certainty Factor method to produce the highest CF value, which will then determine the suitable learning style for the student. The results of the black- box method testing within the system, using items 07 to 12, prove that the system can determine a student's learning style and provide learning recommendations based on that style. However, the accuracy of calculations diminishes when the number of questions is increased, leading to less precise results.
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Linda Rahayu, Rizal Rizal · Router · 2025
An expert system is a computer program designed to imitate the decision-making ability of an expert in a particular field, combining knowledge and rules obtained from experts to diagnose problems, provide advice, or make complex decisions, especially in dental diseases, so this requires the design of an expert system application for website-based dental disease diagnosis with a UML model for users who support the diagnostic process using the certainty factor method, in terms of the explanation of the certainty factor which has a concept based on symptoms and diagnoses from the weight of an expert's value and the user's value, then calculated with the formula in CF, the final result is the creation of a website-based dental disease diagnosis expert system.
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Jing Fan, Yusufujiang Meiliya, Shunchuan Wu · Geomatics · 2025
The southwestern region of China is highly susceptible to landslides due to steep terrain, fractured geology, and intense rainfall. This study focuses on the Xiluodu Reservoir area in Yunnan Province and applies Geographic Information System (GIS) techniques together with ten key spatial factors—such as slope, lithology, elevation, and distance to rivers—to perform a quantitative landslide risk assessment. In addition to the individual Certainty Factor (CF) and Logistic Regression (LR) models, we developed an integrated CF–LR coupled model to overcome their respective limitations: the CF model’s sensitivity to specific factor attributes but neglect of factor interactions, and the LR model’s robust weight estimation but weak representation of attribute heterogeneity. By combining these strengths, the CF–LR model achieved superior predictive performance (AUC = 0.804), successfully capturing 92.5% of historical landslide events within moderate-to-high risk zones. The results show that lithology, slope angle, and proximity to rivers and roads are dominant controls on susceptibility, with landslides concentrated on soft rock slopes of 30–40° and within 600–900 m of rivers. Compared with previous coupled approaches in similar mountainous reservoir settings, our CF–LR model provides a more balanced and interpretable framework, enhancing both classification accuracy and practical applicability. These findings demonstrate that GIS-based CF–LR integration is a novel and reliable tool for landslide susceptibility mapping, offering important technical support for disaster prevention and risk management in large reservoir regions.
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Andre Gunawan · Journal of Computer Scine and Information Technology · 2022
Health is one of the basic human needs of many people who pay little attention to health, especially in dental and oral health because dental and oral diseases can attack anyone and at any time. Therefore, the need for fast and precise information from a dentist is needed according to the symptoms of the disease experienced by the patient. There are many factors that make it rare for someone to do an examination and consult a dentist, including a lack of attention or awareness of dental and oral health, the high costs that must be spent for consultations, long queues that make patients uncomfortable waiting. The existence of information system technology is very influential on the progress of the Assalam Dental Clinic. Using the Expert System Certainty Factor Method and the ADDIE model helps doctors recognize the types of dental disease experienced by patients online. The Certainty Factor method is a method for proving whether a fact is certain or uncertain in the form of a metric which is usually used in expert systems. While the Analysis Design Develop Implement Evaluate (ADDIE) model is one of the systematic learning design models, this model is developed or arranged programmatically. The results of the research based on the calculations that have been carried out by means of a combination get the results of dental disease diagnoses with a high percentage level.
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