The ever-growing popularity of online map services and their wide deployment in smartphones and car-navigation systems have led to extensive use of location-based services. One of the most popular classes of such services is k-nearest neighbor (kNN) queries where users search for geographical points of interests (e.g., restaurants) and the corresponding directions and travel times to these loca...

In the k-nearest neighbor (KNN) classifier, nearest neighbors involve only labeled data. That makes it inappropriate for the data set that includes very few labeled data. In this paper, we aim to solve the classification problem by applying transduction to the KNN algorithm. We consider two groups of nearest neighbors for each data point — one from labeled data, and the other from unlabeled dat...

Indonesia is in the fourth position of countries with most smartphone users worldwide. Smartphones are needed today's modern times. also used not only for long-distance communication but carrying out daily work. currently study and work become entertainment to play. Therefore, smartphones very much sought after suitability who carry their activities. So this research helpful find that support a...

BACKGROUND Coronary heart disease (CHD) is a common cardiovascular disease that is extremely harmful to humans. In Traditional Chinese Medicine (TCM), the diagnosis and treatment of CHD have a long history and ample experience. However, the non-standard inquiry information influences the diagnosis and treatment in TCM to a certain extent. In this paper, we study the standardization of inquiry i...

Closed Form is a propagation based matting algorithm, functioning well on images with good propagation . The deficiency of the Closed Form method is that for complex areas with poor image propagation , such as hole areas or areas of long and narrow structures. The right results are usually hard to get. On these areas, if certain flags are provided, it can improve the effects of matting. In this...

AdaBoost is an excellent committee-based tool for classification. However, its effectiveness and efficiency in multiclass categorization face the challenges from methods based on support vector machine SVM , neural networks NN , naı̈ve Bayes, and k-nearest neighbor kNN . This paper uses a novel multi-class AdaBoost algorithm to avoid reducing the multi-class classification problem to multiple tw...

Automatic classification of text documents, one of essential techniques for Web mining, has always been a hot topic due to the explosive growth of digital documents available on-line. In text classification community, k-nearest neighbor (kNN) is a simple and yet effective classifier. However, as being a lazy learning method without premodelling, kNN has a high cost to classify new documents whe...

This paper presents a new solution for choosing the K parameter in the k-nearest neighbor (KNN) algorithm, the solution depending on the idea of ensemble learning, in which a weak KNN classifier is used each time with a different K, starting from one to the square root of the size of the training set. The results of the weak classifiers are combined using the weighted sum rule. The proposed sol...