Clustering search results. Part II: search engines for highly structured databases

Abstract

Purpose

The purpose of this paper is to examine clustering search results.

Design/methodology/approach

Compares the clustering features of Web of Science, Scopus and Google Scholar extensively.

Findings

Producers who offer clustering, despite certain deficiencies, deserve acknowledgement for implementing these tools which facilitate the search process as well as understanding the anatomy of the databases.

Originality/value

The paper illustrates the best clustering solutions for highly structured databases, such as indexing/abstracting databases, publishers' archives and MARC‐based or XML‐based online public access catalogues.

Citation

Jacsó, P. (2007), "Clustering search results. Part II: search engines for highly structured databases", Online Information Review, Vol. 31 No. 2, pp. 234-241. https://doi.org/10.1108/14684520710747257