Multi-Feature Index Tree (MFI-Tree), a new indexing structure, is proposed to index multiple high-dimensional features of video data for video retrieval through example. MFI-Tree employs tree structure which is beneficial for the browsing application, and retrieves the last level cluster nodes in retrieval application to improve the performance. Aggressive Decided Distance for kNN (ADD-kNN) sea...

With the development of the Internet, the technology of location fingerprint is widely used because of the advantage in indoor positioning performance of complex environment. K neighbor algorithm based on signal strength is a common position fingerprint matching algorithm. This paper firstly introduces the KNN fingerprint localization algorithm, and points out the deficiency of the algorithm. T...

We present Stochastic Neighbor Compression (SNC), an algorithm to compress a dataset for the purpose of k-nearest neighbor (kNN) classification. Given training data, SNC learns a much smaller synthetic data set, that minimizes the stochastic 1-nearest neighbor classification error on the training data. This approach has several appealing properties: due to its small size, the compressed set spe...

Approximate kNN (k-nearest neighbor) techniques using binary hash functions are among the most commonly used approaches for overcoming the prohibitive cost of performing exact kNN queries. However, the success of these techniques largely depends on their hash functions’ ability to distinguish kNN items; that is, the kNN items retrieved based on data items’ hashcodes, should include as many true...

This article reports on a modification of the user-kNN algorithm that measures the similarity between users based on the similarity of text reviews, instead of ratings. We investigate the performance of text semantic similarity measures and we evaluate our text-based user-kNN approach by comparing it to a range of ratings-based approaches in a ratings prediction task. We do so by using datasets...

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 ...

Because of it is applicability in various field, multi-instance learning or multi-instance problem becoming more popular in machine learning research field. Different from supervised learning, multi-instance learning related to the problem of classifying an unknown bag into positive or negative label such that labels of instances of bags are ambiguous. This paper uses and study three different ...

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 ...