Performance Oriented Query Processing In GEO Based Location Search Engines

TL;DR

This paper addresses the challenge of efficient query processing in scalable geographic search engines by proposing new algorithms that combine text and spatial data processing, evaluated on real-world data.

Contribution

It introduces novel algorithms for geographic query processing, integrating them into existing search engines to improve efficiency and scalability.

Findings

Algorithms significantly reduce query processing time.

Effective integration with existing web search systems.

Validated on large datasets and real query traces.

Abstract

Geographic location search engines allow users to constrain and order search results in an intuitive manner by focusing a query on a particular geographic region. Geographic search technology, also called location search, has recently received significant interest from major search engine companies. Academic research in this area has focused primarily on techniques for extracting geographic knowledge from the web. In this paper, we study the problem of efficient query processing in scalable geographic search engines. Query processing is a major bottleneck in standard web search engines, and the main reason for the thousands of machines used by the major engines. Geographic search engine query processing is different in that it requires a combination of text and spatial data processing techniques. We propose several algorithms for efficient query processing in geographic search engines, integrate them into an existing web search query processor, and evaluate them on large sets of real data and query traces.