Kinetic Models for Topological Nearest-Neighbor Interactions
نویسندگان
چکیده
منابع مشابه
Kinetic Reverse k-Nearest Neighbor Problem
This paper provides the first solution to the kinetic reverse k-nearest neighbor (RkNN) problem in R, which is defined as follows: Given a set P of n moving points in arbitrary but fixed dimension d, an integer k, and a query point q / ∈ P at any time t, report all the points p ∈ P for which q is one of the k-nearest neighbors of p.
متن کاملNearest Neighbor and Reverse Nearest Neighbor Queries for Moving Objects
With the proliferation of wireless communications and the rapid advances in technologies for tracking the positions of continuously moving objects, algorithms for efficiently answering queries about large numbers of moving objects increasingly are needed. One such query is the reverse nearest neighbor (RNN) query that returns the objects that have a query object as their closest object. While a...
متن کاملNonlinear Diffusion Limit for a System with Nearest Neighbor Interactions
We consider a system of interacting diffusions. The variables are to be thought of as charges at sites indexed by a periodic one-dimensional lattice. The diffusion preserves the total charge and the interaction is of nearest neighbor type. With the appropriate scaling of lattice spacing and time, a nonlinear diffusion equation is derived for the time evolution of the macroscopic charge density....
متن کاملSecond-Order Word Embeddings from Nearest Neighbor Topological Features
We introduce second-order vector representations of words, induced from nearest neighborhood topological features in pre-trained contextual word embeddings. We then analyze the effects of using second-order embeddings as input features in two deep natural language processing models, for named entity recognition and recognizing textual entailment, as well as a linear model for paraphrase recogni...
متن کاملNearest Neighbor
Over the last decade, an immense amount of data has become available. From collections of photos, to genetic data, and to network traffic statistics, modern technologies and cheap storage have made it possible to accumulate huge datasets. But how can we effectively use all this data? The ever growing sizes of the datasets make it imperative to design new algorithms capable of sifting through th...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Statistical Physics
سال: 2017
ISSN: 0022-4715,1572-9613
DOI: 10.1007/s10955-017-1882-z