Continuously monitoring kNN queries in a highly dynamic environment has become a necessity to many recent location-based applications. In this paper, we study the problem of continuous kNN query on the dataset with an in-memory grid index. We first present a novel data access method – CircularTrip. Then, an efficient CircularTrip-based continuous kNN algorithm is developed. Compared with the ex...

A three dimensional quantitative structure activity relationship (3D QSAR) using k nearest neighbor molecular field analysis (kNN MFA) method was performed on a series of arylbenzofuran derivatives as H3-receptor antagonists. This study was performed with 29 compounds (data set) using sphere exclusion (SE) algorithm and random selection method for the division of the data set into training and ...

The enormous growth and usage of social networks offer positive ways to any business by sharing the emotions, feelings and experiences. Web users are benefited with valuable online reviews. To utilize the reviews effectively, researchers are working on necessary methods and ideas such as classification of positive and negative sense of reviews, ranking the facet in the reviews to make the effec...

The k-Nearest Neighbor (kNN) method of forest attribute estimation and mapping has become an integral part of national forest inventory methods in Finland in the last decade. This success of kNN method in facilitating multi-source inventory has encouraged trials of the method in the Great Lakes Region of the United States. Here we present results from applying the method to Landsat TM and ETM+ ...

ML-kNN is a well-known algorithm for multi-label classification. Although effective in some cases, ML-kNN has some defect due to the fact that it is a binary relevance classifier which only considers one label every time. In this paper, we present a new method for multi-label classification, which is based on lazy learning approaches to classify an unseen instance on the basis of its k nearest ...