1 research outputs found
Accessing very high dimensional spaces in parallel
Access methods are a fundamental tool on Information Retrieval. However,
most of these methods suffer the problem known as the curse of dimensionality when
they are applied to objects with very high dimensionality representation spaces, such
as text documents. In this paper we introduce a new parallel access method that uses
several graphs as distributed index structure and a kNN search algorithm. Two parallel
versions of the search method are presented, one based on master–slave scheme and
the other based on a pipeline. A thorough experimental analysis on different datasets
shows that our method can process efficiently large flows of queries, compete with
other parallel algorithms and obtain at the same time very high quality results.This research has been supported by the CICYT project TIN2014-53495-R of the
Ministerio de EconomÃa y Competitividad