OLAP Queries Context-Aware Recommender System

被引：3

作者：

Negre, Elsa ^{[1
]}

Ravat, Franck ^{[2
]}

Teste, Olivier ^{[2
]}

机构：

[1] Paris Dauphine Univ, PSL Res Univ, LAMSADE, CNRS,UMR 7243, Paris, France

[2] Univ Toulouse, IRIT, CNRS, UMR 5505, Toulouse, France

来源：

DATABASE AND EXPERT SYSTEMS APPLICATIONS (DEXA 2018), PT II | 2018年 / 11030卷

关键词：

D O I：

10.1007/978-3-319-98812-2_9

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

It becomes hard and tedious to easily obtain relevant decisional data in large data warehouses. In order to ease user exploration during on-line analytical processing analysis, recommender systems are developed. However some recommendations can be inappropriate (irrelevant queries or non-computable queries). To overcome these mismatches, we propose to integrate contextual data into the recommender system. In this paper, we provide (i) an indicator of obsolescence for OLAP queries and (ii) a context-aware recommender system based on a contextual post-filtering for OLAP queries.

引用

页码：127 / 137

页数：11

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