Archivio istituzionale della ricerca dell'Università degli Studi di Palermo
IRIS è il sistema di gestione integrata dei dati della ricerca (persone, pubblicazioni, progetti, attività) adottato dall’Università di Palermo, e ha lo scopo di raccogliere, conservare, documentare, e diffondere ad accesso aperto le informazioni relative alla produzione scientifica degli autori afferenti all’Ateneo.
EnglishWe present visual re-ranking, an interactive visualization technique for multi-aspect information retrieval. In multi-aspect search, the information need of the user consists of more than one aspect or query simultaneously. While visualization and interactive search user interface techniques for improving user interpretation of search results have been proposed, the current research lacks understanding on how useful these are for the user: whether they lead to quantifiable benefits in perceiving the result space and allow faster, and more precise retrieval. Our technique visualizes relevance and document density on a two-dimensional map with respect to the query phrases. Pointing to a location on the map specifies a weight distribution of the relevance to each of the query phrases, according to which search results are re-ranked. User experiments compared our technique to a uni-dimensional search interface with typed query and ranked result list, in perception and retrieval tasks. Visual reranking yielded improved accuracy in perception, higher precision in retrieval and overall faster task execution. Our findings demonstrate the utility of visual re-ranking, and can help designing search user interfaces that support multi-aspect search.
Klouche, K., Ruotsalo, T., Micallef, L., Andolina, S., & Jacucci, G. (2017). Visual re-ranking for multi-aspect information retrieval. In CHIIR 2017 - Proceedings of the 2017 Conference Human Information Interaction and Retrieval (pp. 57-66). Association for Computing Machinery, Inc [10.1145/3020165.3020174].
| Data di pubblicazione: | 2017 | |
| Titolo: | Visual re-ranking for multi-aspect information retrieval | |
| Autori: | ||
| Citazione: | Klouche, K., Ruotsalo, T., Micallef, L., Andolina, S., & Jacucci, G. (2017). Visual re-ranking for multi-aspect information retrieval. In CHIIR 2017 - Proceedings of the 2017 Conference Human Information Interaction and Retrieval (pp. 57-66). Association for Computing Machinery, Inc [10.1145/3020165.3020174]. | |
| Abstract: | We present visual re-ranking, an interactive visualization technique for multi-aspect information retrieval. In multi-aspect search, the information need of the user consists of more than one aspect or query simultaneously. While visualization and interactive search user interface techniques for improving user interpretation of search results have been proposed, the current research lacks understanding on how useful these are for the user: whether they lead to quantifiable benefits in perceiving the result space and allow faster, and more precise retrieval. Our technique visualizes relevance and document density on a two-dimensional map with respect to the query phrases. Pointing to a location on the map specifies a weight distribution of the relevance to each of the query phrases, according to which search results are re-ranked. User experiments compared our technique to a uni-dimensional search interface with typed query and ranked result list, in perception and retrieval tasks. Visual reranking yielded improved accuracy in perception, higher precision in retrieval and overall faster task execution. Our findings demonstrate the utility of visual re-ranking, and can help designing search user interfaces that support multi-aspect search. | |
| ISBN: | 978-1-4503-4677-1 | |
| Digital Object Identifier (DOI): | 10.1145/3020165.3020174 | |
| Settore Scientifico Disciplinare: | Settore INF/01 - Informatica Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni | |
| Appare nelle tipologie: | 2.07 Contributo in atti di convegno pubblicato in volume |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| [2017][CHIIR] Visual Re-Ranking for Multi-Aspect Information Retrieval.pdf | Versione Editoriale | Administrator Richiedi una copia |
http://hdl.handle.net/10447/389315
Copyright © 2021