Collaborative filtering (CF) is the most widely used and successful approach for personalized service recommendations. Among the collaborative recommendation approaches, neighborhood based approaches enjoy a huge amount of popularity, due to their simplicity, justifiability, efficiency and stability. Neighborhood based collaborative filtering approach finds K nearest neighbors to an active user...

BACKGROUND We examined the relationship between overweight in preschool children and three environmental factors--the proximity of the children's residences to playgrounds and to fast food restaurants and the safety of the children's neighborhoods. We hypothesized that children who lived farther from playgrounds, closer to fast food restaurants, and in unsafe neighborhoods were more likely to b...

A novel solution is presented to the Nearest Neighbor Problem that is specifically tailored for determining correspondences within the Iterative Closest Point Algorithm. The reference point set P is preprocessed by calculating for each point ~pi 2 P that neighborhood of points which lie within a certain distance of ~pi. The points within each -neighborhood are sorted by increasing distance to t...

Time-frequency analysis is performed for chaotic flow with a power spectrum estimator based on the phase-space neighborhood. The relation between the reference phase point and its nearest neighbors is demonstrated. The nearest neighbors, representing the state recurrences in the phase space reconstructed by time delay embedding, actually cover data segments with similar wave forms and thus poss...

Consider a set of N objects, consisting of Ni objects originating from population Ai, i = 1,. . . , k, so that N = Zf-, Ni. In order to classify the set of N objects, we measure a variable with pdf A for objects originating from population Ai. Let x1,x2;. .,x, be the measured values of the N objects, which are assumed to be independent. Now consider the N-tuple Gi = (gljt g2j, * * ’ 3 Sp ’ ’ ’ ...

OBJECTIVE To determine the extent to which neighborhood needs (socioeconomic deprivation and vehicle availability) are associated with two criteria of food environment access: 1) distance to the nearest food store and fast food restaurant and 2) coverage (number) of food stores and fast food restaurants within a specified network distance of neighborhood areas of colonias, using ground-truthed ...

The recent progress in describing affinities between images or objects by means of shape, appearance or texture allows the exploitation of inherently emerging redundancies for improvement of retrieval tasks. We propose a two-way normalization and analysis scheme which aims on (a) modeling object interdependence by neighborhood incorporation and (b) retrieval improvement by subsequent analysis f...

Nowadays a wide variety of clustering methods exist. The critical decision of what keywords will be used in the representation of the collection is considered in those methods. In this paper we deal with the problem of clustering a set of short texts from an specific domain. Thus, the problem become to be more complex because of the small number of terms that can be used in term selection proce...

Prediction-error expansion (PEE) is an important reversible data hiding technique, which can hide large messages into digital media with little distortion. In this paper, we propose a nearest neighborhood pixel prediction algorithm (NNP) for reversible data hiding algorithms based on Chinese Remainder Theorem (CRT), in which a rhombus prediction is applied in NNP, and prediction errors, the dif...

Image thresholding plays an important role in image segmentation. This paper presents a novel fuzzy clustering based image thresholding technique, which incorporates the spatial neighborhood information into the standard fuzzy c-means (FCM) clustering algorithm. The prior spatial constraint, which is defined as weight in this paper, is inspired by the k-nearest neighbor (k-NN) algorithm and is ...