λ-diverse nearest neighbors browsing for multidimensional data

λ-Diverse Nearest Neighbors Browsing for Multidimensional Data

Traditional search methods try to obtain the most relevant information and rank it according to the degree of similarity to the queries. Diversity in query results is also preferred by a variety of applications since results very similar to each other cannot capture all aspects of the queried topic. In this work, we focus on the λ-diverse k-nearest neighbor search problem on spatial and multi-d...

Finding Data Broadness Via Generalized Nearest Neighbors

A data object is broad if it is one of the k-Nearest Neighbors (k-NN) of many data objects. We introduce a new database primitive called Generalized Nearest Neighbor (GNN) to express data broadness. We also develop three strategies to answer GNN queries efficiently for large datasets of multidimensional objects. The R*-Tree based search algorithm generates candidate pages and ranks them based o...

Positioning for Online Nearest Neighbors

Density Based k-Nearest Neighbors Clustering Algorithm for Trajectory Data

With widespread availability of low cost GPS, cellular phones, satellite imagery, robotics, Web traffic monitoring devices, it is becoming possible to record and store data about the movement of people and objects at a large amount. While these data hide important knowledge for the enhancement of location and mobility oriented infrastructures and services, by themselves, they demand the necessa...

Refined Shared Nearest Neighbors Graph for Combining Multiple Data Clusterings

We recently introduced the idea of solving cluster ensembles using a Weighted Shared nearest neighbors Graph (WSnnG). Preliminary experiments have shown promising results in terms of integrating different clusterings into a combined one, such that the natural cluster structure of the data can be revealed. In this paper, we further study and extend the basic WSnnG. First, we introduce the use of...