Grouper: a dynamic clustering interface to Web search results

Abstract

Users of Web search engines are often forced to sift through the long ordered list of document "snippets" returned by the engines. The IR community has explored document clustering as an alternative method of organizing retrieval results, but clustering has yet to be deployed on most major search engines. The NorthernLight search engine organizes its output into "custom folders" based on pre-computed document labels, but does not reveal how the folders are generated or how well they correspond to users' interests.In this paper, we introduce Grouper -an interface to the results of the HuskySearch meta-search engine, which dynamically groups the search results into clusters labeled by phrases extracted from the snippets. In addition, we report on the first empirical comparison of user Web search behavior on a standard ranked-list presentation versus a clustered presentation. By analyzing HuskySearch logs, we are able to demonstrate substantial differences in the number of documents followed, and in the amount of time and effort expended by users accessing search results through these two interfaces.

Experts dans le domaine, experts en internet

“…Ils ont constaté que les participants ont préféré l'interface avec des catégories et étaient 50 % plus rapides dans la découverte de l'information avec la première interface. Ces résultats corroborent les études de (Zamir, 1999). Ce dernier montre que le temps moyen d'une recherche en utilisant une interface de visualisation de l'information est de 72,4 secondes/question alors qu'il est de 99,7 secondes/question pour une interface classique.…”

A Framework for Grouping and Summarizing Keyword Search Results

“…Our approach is different, in that, we propose grouping keyword search results to help users receive the general picture of the results of their queries. A comparison between a flat ranked list of results and a clustering web search interface shows that the users of the clustering approach view more documents and spend less time per document [21]. However, the relevance of the viewed documents is unknown.…”

User Evaluation Methods for Visual Web Search Interfaces

“…There have been numerous studies on the abilities of people to craft queries and evaluate search results based solely on search engine logs [13,31]. For visual Web search interfaces, it is vitally important to not just log the queries, but also to log how the interactive visual features of the system are being used [37].…”