Nearest Neighbour Searching in Binary Search Trees: Simulation of a Multiprocessor System

Abstract

This paper describes the simulation of a nearest neighbour searching algorithm for document retrieval using a pool of microprocessors. The documents in a database are organised in a multi‐dimensional binary search tree, and the algorithm identifies the nearest neighbour for a query by a backtracking search of this tree. Three techniques are described which allow parallel searching of the tree. A PASCAL‐based, general purpose simulation system is used to simulate these techniques, using a pool of Transputer‐like microprocessors with three standard document test collections. The degree of speed‐up and processor utilisation obtained is shown to be strongly dependent upon the characteristics of the documents and queries used. The results support the use of pooled microprocessor systems for searching applications in information retrieval.

New techniques for best-match retrieval

“…Recently, there have been attempts to extend techniques for informational retrieval to multiprocessor architectures [16,26,28,371. Stewart and Willett [36], for example, describe three techniques that allow parallel searching of k -cl trees. Their results support the use of multiprocessor systems for searching applications in information retrieval.…”

“…One way of computing the similarity between a document and the query is to count the number of terms in common between them; the documents presented to the user first are those that contain the greatest number of terms specified in the query. The best-match searching procedure in such ranked output retrieval systems identifies the terms in common between the query and each of the documents in the file [36]. In molecular biology, to gain information about a newly sequenced protein, biologists compare the protein's amino acid sequence against those of many known proteins, searching for ones with very similar sequences.…”

Parallel computing in information retrieval – an updated review

“…Vector Processing. Stewart and Willett [80] describe an algorithm for nearest neighbour search using a multi-dimensional binary search tree, using networked …”

“…Given the variety of approaches in this section we will not attempt to describe the interaction between architecture, the algorithms and the types of query parallelism used. [80] described an algorithm for nearest neighbour search using a multi-dimensional binary search tree, using networked microprocessors. Documents are represented by vectors, as is the query: the vector contains identifiers of terms in that document.…”

Efficiency of text scanning in bibliographic databases using microprocessor-based, multiprocessor networks

“…Work in Sheffield over the last few years has considered the use of SIMD architectures for text retrieval [8,33], and the availability of transputers provided an opportunity to investigate the potential of MIMD parallelism for this application. Stewart and Willett have recently reported a simulation study of the implementation of a binary-tree based nearest neighbour searching algorithm for document databases on a transputer system [39]. The simulation demonstrated that there was substantial scope for increasing the speed of searching but that the precise degree of speed-up was crucially dependent upon the way in which the parallelism in the searching task was implemented, and upon the characteristics of the documents.…”