Katsutoshi Kanamori's research while affiliated with Tokyo University of Science and other places

Publications (26)

Chapter
A significant amount of microarray gene expression data is available on the Internet, and researchers are allowed to analyze such data freely. However, microarray data includes thousands of genes, and analysis using conventional techniques is too difficult. Therefore, selecting informative gene(s) from high-dimensional data is very important. In th...
Chapter
This study was performed to extract rules and factors for reducing body fat mass and to compare Inductive Logic Programming (ILP) and common classifiers to provide necessary steps for the healthcare system. Many researchers have focused on lifestyle-related diseases; however, few have attempted to extract rules and factors for decreasing body fat m...
Article
A significant amount of microarray gene expression data is available on the Internet, and researchers are allowed to analyze such data freely. However, microarray data includes thousands of genes, and analysis using conventional techniques is too difficult. Therefore, selecting informative gene(s) from high-dimensional data is very important. In th...
Conference Paper
This study aims to classify corporate values among Japanese companies based on their corporate social responsibility (CSR) performances. Since there are many attributes in CSR, feature selection with decision tree criteria is used to select the attributes that can classify corporate values. The feature selection found that 41 % of 37 total attribut...
Conference Paper
The relationship between corporate social responsibility (CSR) and financial performance is complex and nuanced. Many studies have reported positive, negative, and neutral impacts of CSR on financial performance. This inconsistency is due to differences in methodologies, approaches, and selection of variables. Rather than focusing on specific varia...
Conference Paper
This study was performed to extract rules for reducing body fat mass so as to prevent lifestyle-related diseases. Lifestyle-related diseases have been increasing in Japan, even among younger people. Body fat mass is related to lifestyle-related diseases. Hence, finding rules for reducing body fat mass is very meaningful. We obtained lifestyle time-...
Conference Paper
Numerous databases of DNA-microarrays are now widely available on the internet. Recently, there has been increasing interest in the analysis of microarray data using machine-learning techniques due to the amount of data, which is too massive for researchers to analyze using conventional techniques. In this study, we propose a method of finding a di...
Article
This study was performed to extract rules and factors for reducing body fat mass and to compare Inductive Logic Programming (ILP) and common classifiers to provide necessary steps for the healthcare system. Many researchers have focused on lifestyle-related diseases; however, few have attempted to extract rules and factors for decreasing body fat m...
Conference Paper
The Japanese understanding of corporate social responsibility (CSR) is linked with the country’s history of industrial pollution. As a result, the top area Japanese companies are addressing is the environment. This study aims to classify the corporate value of Japanese companies calculated by the Ohlson model based on environmental efforts using se...
Conference Paper
Full-text available
This study model an integration between agent-based simulation and machine learning in order to have a comprehensive result of behavior prediction. Model are applied to a case of customer churning in a subscription-based business. To have a good model for behavior prediction, dynamic simulation based on social structure is required. In this study,...
Conference Paper
Land-cover classification can construct a land-use map to analyze satellite images using machine learning. However, supervised machine learning requires a lot of training data since remote sensing data is of higher resolution that reveals many features. Therefore, this study proposed a method to generate self-training data from a small amount of tr...
Article
Many global and environmental applications require land-use and land-cover information. At present, imagery analysis can classify remote-sensing data using supervised learning. However, existing learning techniques require a large number of training samples, which is not realistic because land cover classification should be used for unknown land. W...
Conference Paper
Full-text available
This paper aims to provide a solution to the prediction of customer defection task in the growing market of cloud software industry. From the original unstructured data from the company, we proposed a procedure to first identify the real defection condition, whether the customer is defecting from the company or merely stop using current product to...
Conference Paper
Full-text available
This paper proposes an estimation of Customer Lifetime Value (CLV) for a cloud-based software company by using machine learning techniques. The purpose of this study is twofold. We classify the customers of one cloud-based software company by using two classifications methods: C4.5 and a support vector machine (SVM). We use machine learning primari...
Article
Personalized recommendation systems can help people find things that interest them and are widely used in developing the Internet or e-commerce. Collaborative filtering (CF) seems to be the most popular technique in recommender systems. However, CF is weak in the process of finding similar users. To resolve these problems, trust-aware recommender s...
Article
This paper describes route-planning algorithms for navigation in amusement parks (e.g. Disneyland). Unlike conventional shortest-path-finding used for traveling salesman problems, the authors provide several algorithms that consider waiting time estimates in real time, exploit the reservation facilities of an attraction such as Fastpass in Disneyla...
Article
This paper presents a high performance virtual screening method for drug design based on machine learning. In drug discovery with computers, drug designers often use docking softwares. They decide the docking between the compound and the protein with the result of docking software, structure of the compound, and any information of the compound. Cur...
Conference Paper
This paper describes flexible route planning for amusement parks (e.g. Disneyland) navigation. Unlike conventional shortest path finding, we provide several types of algorithms that consider waiting time estimation in real time, exploit the reservation facility of an attraction such as Fast Pass in Disneyland, and balance a series of enjoyment type...
Article
This paper proposes a new approach to classification of docking between compounds and proteins for drug design virtual screening. Currently, docking software programs often use real numbers as docking scores; but due to their predictive accuracy, it is difficult for biologists to use such scores in realistic experiments. In contrast, our approach u...
Article
Many amusement parks adopt a reservation service(e.g. Fast pass at Disneyland) , that effectively reduce the waiting time for visitors. Even if visitors do use the reservation service, the traveling time may be long, depending on the order in which users visit the attractions. We think that people need a new route search algorithm to enhance the re...
Article
The purpose of our work is to achieve creative knowledge processing. In this paper, we focus on the formulation of concept generation and its use in problem solving. We propose a method for solving a problem by generating new concepts that have never appeared in existing knowledge. We propose Creative Problem Solving, which can derive a goal state...

Citations

... In 2017,K, Nishiwaki, et al [80]. machine learning technology of random forest to develop a gene selection method. ...
... The methodology is divided into four steps: 1) normalization 2) merging of microarray data 3) pre-selection and 4) disease-related genes selection. For pre-selection of genes a threshold was introduced to remove genes which are less important and also reduces the processing time [85]. All the hyperparameters for random forest were kept same as proposed in original work. ...
... Inductive logic programming [2] has been employed successfully in extracting comprehensible and accurate rules in both scientifically and industrially relevant problems [3,4]. It provides an outstanding basis for learning in multi-relational domains such as medicine [5][6][7], molecular biology and chemistry [8,9], as well as in other areas like software engineering [10,11]. ...
... This paper aims to build up solutions to help restaurants that with low ratings to improve their ratings on "Yelp" based on reviews and business features like opening hours, noise Level and parking space or Wi-Fi. We choose to implement two different methods, multinomial logistic regression and random forest, to obtain the most important attributions that affect the business' ratings [1,2]. Therefore, the goal is to find out whether there are some crucial attributions that could make one restaurant obtain a higher rate or better reviews. ...
... Very recent examples of AI research (e.g. Vo, Cao and Ho, 2016;Hidayati et al. 2016;Lee, Chen, and Cai, 2016) reinforce this point, for current AI is still focused on automating what is largely verballyarticulated decision making. We know machines possessing limited behaviouristic sense as they react to stimuli, are able to successfully deal with some forms of STK. ...
... This is the reason behind the implementation of multiple algorithms for our data, while using a hold-out "test set" of data to evaluate performance and select the winner. [43] Using traditional ML model, we are not finding any satisfactory results. For further improvement of the results, we apply hyper parameter tuning. ...
... Accuracy reflects the percentage of correctly identified cases [8], [45], [95] and represents an overall performance that is widely adopted [95], represent almost 50% of all occurrences. The accuracy is calculated using the ratio between the total number of correct predictions and the total number of predictions and has been widely employed in several studies [25], [26], [40], [45], [46], [54], [69], [71], [72], [76], [85], [98], [101], [103]- [105], [108], [109], [111]- [118], [118], [120]- [122], [124]. This finding could be attributed to the intuitive interpretation of the indicator and easy calculation. ...
... In order to analyze the spread of Cutaneous Leishmaniasis in central Iran, Rajabi et al. [59] proposed an ABM to simulate the dynamics of spread based on a Geographic Automata System, the results of which were analyzed by means of Bayesian modeling. In a similar approach, Hayashi et al. [60] used Decision Trees in order to achieve comprehensive behavior prediction in the case of customer churning in a subscription-based business. With a similar objective, R. Vahdati et al. [61] also used Decision Trees to understand how factors, such as climate, ecology, human behavior, and population dynamics, interacted to affect human survival and dispersal from Africa in the Late Pleistocene age. ...
... We consider the addition of edges between different-type vertices of the network as a less invasive treatment method. A typical example of the use of this kind of treatment in real networks is the suggestion of new friendship relations in social networks, such as those used in recommendation systems [8,9]. By adding edges between vertices of different groups, a super-graph containing the original graph is built. ...
... For example, a method to find the shortest route considering the waiting time in a zoo have been proposed [1]. Minimizing the total required time of the route considering the waiting time and the reservation system in an amusement park has been also proposed [2], [3]. These studies solve the problem that extends a traveling salesman problem (TSP). ...