This paper proposes a novel language in order to explore the results retrieved by several internet search services and search engines that cluster retrieved documents. The goal of this work, rooted in the new context of Search Computing, is to offer users a tool to discover relevant hidden relationships between clustered documents. When the same query is submitted to distinct search services, they may produce partially overlapped clustered results, where clusters identified by distinct labels collect some common documents. Moreover, clusters with similar labels, but containing distinct documents, may be produced as well. In such a situation, it may be useful to compare, combine, and rank the cluster contents, to filter out relevant documents. The proposed language is composed of several operators that can be used in order to combine groups of clusters.
['Alessandro Campi', 'Stefania Ronchi']
The Role of Clustering in Search Computing