Interactive Query Recommendation Assistant

Author

Khemiri, Rym ; Bentayeb, Fadila

Author_Institution

ERIC Lab., Univ. of Lyon, Bron, France

fYear

2012

Firstpage

93

Lastpage

97

Abstract

When searching information, a first and crucial step is queries formulations. However it is a hard task for decision makers notably in related data warehousing fields, where queries are very heterogeneous and cannot be interpreted easily. This paper presents a new approach to assist users to formulate their queries by exploiting their past querying experiences. Thus, a user can incrementally construct each of his/her queries by visualizing and taking lessons from how other users have carried out their querying tasks. The visualization and the assistance given to the user is based on frequent itemsets extracted from past queries connected to his/her current query in construction.

Keywords

data mining; data visualisation; data warehouses; interactive systems; query processing; recommender systems; data visualization; data warehousing; decision making; frequent itemset extraction; heterogeneous query formulations; information search; interactive query recommendation assistant; Context; Data mining; Data warehouses; Engines; Itemsets; Marketing and sales; Apriori; Data warehouse; Decision Queries; Frequent Itemsets Mining; Interactive Recommendation;

fLanguage

English

Publisher

ieee

Conference_Titel

Database and Expert Systems Applications (DEXA), 2012 23rd International Workshop on

Conference_Location

Vienna

ISSN

1529-4188

Print_ISBN

978-1-4673-2621-6

Type

conf

DOI

10.1109/DEXA.2012.12

Filename

6327409