Search Result Clustering Based on Query Context

• Autorzy: Meina M. , Nguyen H. S.

Identyfikatory

DOI

10.3233/FI-2015-1179

• Języki publikacji: EN

Abstrakty

EN

This paper introduces a novel, interactive and exploratory, approach to information retrieval (search engines) based on clustering. Presented method allows users to change the clustering structure by applying a free-text clustering context query that is treated as a criterion for documentto- cluster allocation. Exploration mechanisms are delivered by redefining the interaction scenario in which the user can interact with data on the level of topic discovery or cluster labeling. In this paper, the presented idea is realized by a graph structure called the Query-Summarize Graph. This data structure is useful in the definition of the similarity measure between the snippets as well as in the snippet clustering algorithm. The experiments on real-world data are showing that the proposed solution has many interesting properties and can be an alternative approach to interactive information retrieval.

Słowa kluczowe

EN

search algorithms; information retrieval; search engines; graph theory; data analysis

• Wydawca: IOS Press
• Czasopismo: Fundamenta Informaticae
• Rocznik: 2015
• Tom: Vol. 137, nr 2
• Strony: 273--290
• Opis fizyczny: Bibliogr. 22 poz., rys., tab.

Twórcy

autor

Meina M.

• Faculty of Mathematics and Computer Science Nicolaus Copernicus University, Toruń, Poland

autor

Nguyen H. S.

• Faculty of Mathematics, Informatics and Mechanics University of Warsaw, Banacha 2, Warsaw, Poland

Bibliografia

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