BSTree: an Incremental Indexing Structure for Similarity Search and Real Time Monitoring of Data Streams

TL;DR

BSTree is an innovative indexing structure for data streams that combines data discretization, B-tree indexing, and LRV pruning to enable efficient similarity search and real-time monitoring.

Contribution

The paper introduces BSTree, a novel incremental indexing method that integrates data discretization, B-tree structures, and LRV pruning for improved data stream analysis.

Findings

Reduces response time for similarity queries

Efficiently manages data streams with incremental updates

Improves real-time monitoring capabilities

Abstract

In this work, a new indexing technique of data streams called BSTree is proposed. This technique uses the method of data discretization, SAX [4], to reduce online the dimensionality of data streams. It draws on Btree to build the index and finally uses an LRV (least Recently visited) pruning technique to rid the index structure from data whose last visit time exceeds a threshold value and thus minimizes response time for similarity search queries.