A game board implementing data mining and Cultural Algorithms

International Journal of Data Mining & Knowledge Management Process, 2012

Cultural algorithms (CA) are inspired from the cultural evolutionary process in nature and use social intelligence to solve problems. Cultural algorithms are composed of a belief space which uses different knowledge sources, a population space and a protocol that enables exchange of knowledge between these sources. Knowledge created in the population space is accepted into the belief space while this collective knowledge from these sources is combined to influence the decisions of the individual agents in solving problems. Classification rules comes under descriptive knowledge discovery in data mining and are the most sought out by users since they represent highly comprehensible form of knowledge. The rules have certain properties which make them useful forms of actionable knowledge to users. The rules are evaluated using these properties represented as objective and subjective measures. Objective measures are problem oriented while subjective measures are more user oriented. Evolutionary systems allow the user to incorporate different rule metrics into the solution of a multi objective rule mining problem. However the algorithms found in the literature allow only certain attributes of the system to be controlled by the user. Research gap exists in providing a complete user controlled system to experiment with evolutionary multi objective classification rule mining. In the current study a Cultural Algorithm Toolkit for Classification Rule Mining (CAT-CRM) is proposed which allows the user to control three different set of parameters. CAT-CRM allows the user to control the evolutionary parameters, the rule parameters as well as agent parameters and hence can be used for experimenting with an evolutionary system, a rule mining system or an agent based social system. Results of experiments conducted to observe the effect of different crossover rates and mutation rates on classification accuracy on a bench mark data set is reported.

IJCSMC, 2019

An analytical, descriptive and perhaps instinctive methodology regarding sourcing out ways to improve business opportunities and technical know-how is incorporated within the scope of Data Mining. Its designation relates to how an event deals with obtaining unprocessed information from vast databases by deeply searching the resourceful highland areas for further processing to qualify valuableness. Its applications are typically employed in facilitating the operations of marketing, sales and services of business though it works more with stable datasets that are kept in the business's threshold of sensitive and discreet information. The essence of its strategies in the modern world includes automated prediction of trends and behavior as well as abstracting initially unknown patterns. Grave utterances concerning the supposedly efficient data mining techniques have been made significant over the years since its discovery. There are still positive and negative remarks about these said techniques claimed to improve business functionalities. The former which may involve how increased processing speeds, lowered costs for storage and better software packages tend to make data mining more economical. And as for the latter, involving how it is deemed unethical to use the processes of data mining as it violates innocent people's privacy. Data mining can be quite an enigma for the inadequately learned individuals and firms due to its cognitive requirements that appear to be highly critical and extensive upon application.

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 2022

This study reviews techniques and algorithm models often used in the analysis of educational data mining. The review in this study is based on previous studies to provide researchers knowledge about trends and challenges analysis Educational data mining in game design meaningful. However, there is a lot of games design developed without analysis Educational data mining which then will not answer the student problem. The analysis needed periodic data and developing the game required actual student conditions, this is a combination inseparable. Determine Research questions, Search Terms, and filtering for the selection and analysis of the article review. There are some student problems on analysis review, namely prediction student performance, student behavior, student at-riks, and student dropout. The number of Articles in the study was 33 with 21 Articles of research and 12 of Article review. The number of studies 8 with percent 38% used techniques Confusion matric with 33% percent ...

Osiris, 2017

The term "Big Data" may serve as a useful marker for particular kinds of questions, practices, and relationships for collecting and using data. Some of the ways of talking about Big Data suggest that there might be something, if not entirely new, then at least importantly different at work in Big Data practices and problem-solving approaches. By using three examples taken from the biomedical sciences-artificial neural networks, the construction of reference genomes, and the usage of the Ensembl database-this essay shows how Big Data practices cannot be understood as mere scaling up of pen-and-paper methods but constitute qualitatively different kinds of knowledge-making practices. These practices are characterized particularly by types of human-computer interaction that are labeled "a feeling for the algorithm."

2001

Abstract. During data mining process users and algorithms could take advantage of the experiences other users or algorithms (agents) had. Implicit Culture is the relation between a set and a group of agents such that the elements of the set behave according to the culture of the group. The goal of a System for Implicit Culture Support (SICS) is to establish an implicit culture phenomenon, namely when the elements of a set behave according to the culture of a generally different group of agents.

International Joint Conference on Artificial Intelligence, 2017

Bio-inspired computational algorithms can be effectively employed to develop games for learning. In the present paper we will introduce different approaches to embed this kind of models in Serious and Educational Games. According to a multi-level description of game design process, bio-inspired computational algorithms can be visible to the user, residing at an external, shell level; can be invisible to the user, residing at the core, internal level; can be employed in the evaluation and tutoring level pertaining to user profiling and supporting learning and teaching processes. This different approaches are explained by introducing some educational games example: BreedBot in which bio-inspired computational algorithms are used to develop the player-game interaction and are explicitly visible by the user; Learn2lead, where these techniques are used to model the game mechanics and are invisible to the user; and Infanzia Digi.tales project in which these techniques are functional to develop smart educational materials by implementing adaptive tutoring systems.

2010

Las técnicas de data mining consisten en la extracción de información a partir de una gran cantidad de datos, mediante el descubrimiento de patrones y regularidades por medio de algoritmos de aprendizaje automático entre otros. Esto puede aplicarse a la clasificación de objetos por medio de imágenes. En la cadena de producción de frutas, el control de calidad es realizado por personas entrenadas, que examinan los frutos mientras éstos avanzan por una cinta transportadora. Luego los clasifican en distintas categoŕıas de acuerdo a diversas caracteŕısticas visuales. En este trabajo presentamos un método para clasificar naranjas por medio de imágenes. El proceso consiste en capturar las imágenes mediante una cámara digital para luego extraer caracteŕısticas y entrenar diversos algoritmos de data mining, los cuales deberán clasificar a la naranja en una de las tres categoŕıas pre-establecidas. Los algoritmos de data mining utilizados son cinco diferentes árboles de decisión (J48, Classif...

Lecture Notes in Computer Science, 2016

Bio-inspired computational algorithms can be effectively employed to develop games for learning. In the present paper we will introduce different approaches to embed this kind of models in Serious and Educational Games. According to a multi-level description of game design process, bio-inspired computational algorithms can be visible to the user, residing at an external, shell level; can be invisible to the user, residing at the core, internal level; can be employed in the evaluation and tutoring level pertaining to user profiling and supporting learning and teaching processes. This different approaches are explained by introducing some educational games example: BreedBot in which bio-inspired computational algorithms are used to develop the player-game interaction and are explicitly visible by the user; Learn2lead, where these techniques are used to model the game mechanics and are invisible to the user; and Infanzia Digi.tales project in which these techniques are functional to develop smart educational materials by implementing adaptive tutoring systems.

O assunto Brasil foi analisado na base de teses francesas DocThèses, compreendendo os anos de 1969 a 1999. Utilizou-se a técnica de Data Mining como ferramenta para obter inteligência e conhecimento. O software utilizado para a limpeza da base DocThèses foi o Infotrans, e, para a preparação dos dados, empregou-se o Dataview. Os resultados da análise foram ilustrados com a aplicação dos pressupostos da Lei de Zipf, classificando-se as informações em trivial, interessante e ruído, conforme a distribuição de freqüência. Conclui-se que a técnica do Data Mining associada a softwares especialistas é uma poderosa aliada no emprego de inteligência no processo decisório em todos os níveis, inclusive o nível macro, pois oferece subsídios para a consolidação, investimento e desenvolvimento de ações e políticas.

The European Proceedings of Social and Behavioural Sciences, 2019

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