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

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.