Clustering search results. Part I: web‐wide search engines

Purpose – The purpose of this paper is to examine clustering search results. Traditionally, search results from professional online information services presented the results in reverse chronological order. Later, relevance ranking was introduced for ordering the display of the hits on the result list to separate the wheat from the chaff. Design/methodology/approach – The need for better presentation of search results retrieved from millions, then billions, of highly unstructured and untagged Web pages became obvious. Clustering became a popular software tool to enhance relevance ranking by grouping items in the typically very large result list. The clusters of items with common semantic and/or other characteristics can guide the users in refining their original queries, to zoom in on smaller clusters and drill down through sub‐groups within the cluster. Findings – Despite its proven efficiency, clustering is not available, except for Ask, in the primary Web‐wide search engines (Windows Live, Yahoo and Google). Originality/value – Smaller, secondary Web‐wide search engines (WiseNut, Gigablast, and especially Exalead) offer good clustering options.