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|Title:||Improving the presentation of search results by multipartite graph clustering of multiple reformulated queries and a novel document representation|
|Citation:||Improving the presentation of search results by multipartite graph clustering of multiple reformulated queries and a novel document representation / N. Lytkin, S. Streltsov, L. Perlovsky, I. Muchnik, S. Petrov // Интернет-математика 2005. Автоматическая обработка веб-данных. — М., 2005.|
|Abstract:||The goal of clustering web search results is to reveal the semantics of the retrieved documents. The main challenge is to make clustering partition relevant to a user’s query. In this paper, we describe a method of clustering search results using a similarity measure between documents retrieved by multiple reformulated queries. The method produces clusters of documents that are most relevant to the original query and, at the same time, represent a more diverse set of semantically related queries. In order to cluster thousands of documents in real time, we designed a novel multipartite graph clustering algorithm that has low polynomial complexity and no manually adjusted hyper–parameters. The loss of semantics resulting from the stem–based document representation is a common problem in information retrieval. To address this problem, we propose an alternative novel document representation, under which words are represented by their synonymy groups.|
|metadata.dc.description.sponsorship:||This work was supported by Yandex grant 110104.|
|Origin:||Интернет-математика 2005: автоматическая обработка веб-данных. — М., 2005|
|Appears in Collections:||Информационный поиск|
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