Minimum threshold determination method based on dataset characteristics in association rule mining

Association rule mining is a technique that is widely used in data mining. This technique is used to identify interesting relationships between sets of items in a dataset and predict associative behavior for new data. Before the rule is formed, it must be determined in advance which items will be involved or called the frequent itemset. In this step, a threshold is used to eliminate items excluded in the frequent itemset which is also known as the minimum support. Furthermore, the threshold provides an important role in determining the number of rules generated. However, setting the wrong threshold leads to the failure of the association rule mining to obtain rules. Currently, user determines the minimum support value randomly. This leads to a challenge that becomes worse for a user that is ignorant of the dataset characteristics. It causes a lot of memory and time consumption. This is because the rule formation process is repeated until it finds the desired number of rules. The value of minimum support in the adaptive support model is determined based on the average and total number of items in each transaction, as well as their support values. Furthermore, the proposed method also uses certain criteria as thresholds, therefore, the resulting rules are in accordance with user needs. The minimum support value in the proposed method is obtained from the average utility value divided by the total existing transactions. Experiments were carried out on 8 specific datasets to determine the association rules using different dataset characteristics. The trial of the proposed adaptive support method uses 2 basic algorithms in the association rule, namely Apriori and Fpgrowth. The test is carried out repeatedly to determine the highest and lowest minimum support values. The result showed that 6 out of 8 datasets produced minimum and maximum support values for the apriori and fpgrowth algorithms. This means that the value of the proposed adaptive support has the ability to generate a rule when viewed from the quality as adaptive support produces at a lift ratio value of > 1. The dataset characteristics obtained from the experimental results can be used as a factor to determine the minimum threshold value.

Minimum Threshold Determination Method based on Dataset Characteristics in Association Rule Mining

The process of extracting data to obtain useful information is known as data mining. Furthermore, one of the promising and widely used techniques for this extraction process is association rule mining. This technique is used to identify interesting relationships between sets of items in a dataset and predict associative behavior for new data. The first step in association rule mining is the determination of the frequent item set that will be involved in the rule formation process. In this step, a threshold is used to eliminate items excluded in the frequent itemset which is also known as the minimum support. Furthermore, the threshold provides an important role in determining the number of rules generated. However, setting the wrong threshold leads to the failure of the association rule mining to obtain rules. Currently, the minimum support value is determined by the user. This leads to a challenge that becomes worse for a user that is ignorant of the dataset characteristics. In this study, a method was proposed to determine the minimum support value based on the characteristics of the dataset. Furthermore, this required certain criteria to be used as thresholds which led to more adaptive rules according to the needs of the user. The results of this study showed that 6 from 8 datasets, obtained a rule with lift ratio > 1 using the minimum threshold value that was determined through this method.

The Core of the Language Consciousness of an Ethnic Group in Diachronic Aspect: Kazakh Associative Dictionaries

The article discusses the possibility of using the data of free associative experiments (SAE) and associative dictionaries, which can serve as a tool of ethno-psycholinguistic, cultural and sociopsychological research to identify the mental and ethno-cultural specificity of language consciousness and language pictures of the world of different ethnic groups, structuring the core of language consciousness (JAS), determining the basic values of society and, in the case of creating such dictionaries in different time periods, they are able to identify the transformation of the mental climate and value priorities of different generations of the same ethnic group. The content of the article is such intra-ethnic comparisons of associative behavior of the representations of the Kazakh ethnos of the modern and Soviet period in the hierarchy of value priorities, their stability and transformation, reflected in the nuclear zones of the language consciousness of young people of two generations with a forty-year interval. On the basis of the coincidence of the basic values in the conceptual center of the core of language consciousness, the article concludes about a certain stability and immutability of cultural, mental and behavioral traditions of the Kazakh ethnic group.

ASSOCIATIVE BEHAVIOR OF MEDICAL STUDENTS IN THE EXPERIMENTAL RESEARCH OF MEDICAL TERMS

Статья представляет собой изложение результатов предварительного эксперимента, связанного с изучением динамических аспектов ассоциативной структуры значения медицинских терминов в индивидуальном сознании студентов медицинского вуза с разной степенью сформированности профессиональных компетенций. Проведенный анализ данных психолингвистического эксперимента позволяет обнаружить закономерности в изменении ассоциативного пространства терминологической единицы в строящемся профессиональном сознании будущего медика. The article shows the results of the preliminary experiment connected to the study of dynamic aspects of the associative structure of medical terms’ meaning in the individual consciousness of medical students with different degree of professional competence. Complex usage of the experiment’s data reveals the regularity in changing of the associative space of a term in the forming professional consciousness of a future doctor.

Word Co-occurrence in Child-directed Speech Predicts Children's Free Word Associations

The free association task has been very influential both in cognitive science and in computational linguistics. However, little research has been done to study how free associations develop in childhood. The current work focuses on the developmental hypothesis according to which free word associations emerge by mirroring the co-occurrence distribution of children's linguistic environment. I trained a distributional semantic model on a large corpus of child language and I tested if it could predict children's responses. The results largely supported the hypothesis: Co-occurrence-based similarity was a strong predictor of children's associative behavior even controlling for other possible predictors such as phonological similarity, word frequency, and word length. I discuss the findings in the light of theories of conceptual development.

Functionalized polysaccharides with aminoguaiacol: a competition between associative behavior and antibacterial and antioxidant activities

In a previous study, we presented the development of a series of functionalized carboxymethylpullulan (CMP) grafted with aminoguaiacol (derivative of guaiacol with known antibacterial and antioxidant activities) leading to CMP-G derivatives with various degrees of substitution [DS(Ga)] from 0.16 to 0.58. Our results have shown the efficiency of the grafting both with the evidence of antioxidant and antibacterial activities (Staphylococcus aureus) of the CMP-G derivatives. Nevertheless, an important result has shown surprisingly that such biological activity was not clearly improved with the DS(Ga) unlike the antioxidant activity. These results were probably correlated with a peculiar associative behavior of the derivative (i.e. amphiphilic character) due to the grafted hydrophobic guaiacol groups leading to preferential intramolecular association which was particularly important in the more concentrated regime (polysoap behavior). To complete this study, we propose here two strategies in order to diminish the associative character and notably the polysoap behavior: (i) decrease the DS(Ga) of CMP derivative with a CMP-G0.05 [grafted with a DS(Ga) = 0.05], (ii) conduct the functionalization onto a more rigid polysaccharide backbone as alginate. Our results show a good correlation of the associative physicochemical behaviors with both antioxidant and antibacterial activities. They also confirm the availability of these strategies mainly for the first one (i.e. CMP-G0.05). The main result indicates that the lower is the DS(Ga), the better is the antibacterial activity thanks to a lower associative character. Finally, this study also shows that the grafting of aminoguaiacol is possible onto another anionic polysaccharide (i.e. alginate).