Paper Info
Title
Empirical knowledge engineering: cognitive aspects in the development of constraint-based recommenders
Abstract
Constraint-based recommender applications provide valuable support in item selection processes related to complex products and services. This type of recommender operates on a knowledge base that contains a deep model of the product assortment as well as constraints representing the company's marketing and sales rules. Due to changes in the product assortment as well as in marketing and sales rules, such knowledge bases have to be adapted very quickly and frequently. In this paper we focus on a specific but very important aspect of recommender knowledge base development: we analyze the impact of different constraint representations on the cognitive effort of a knowledge engineer to successfully complete certain knowledge acquisition tasks. In this context, we report results of an initial empirical study and provide first basic recommendations regarding the design of recommender knowledge bases.
Year
DOI
Venue
2010
10.1007/978-3-642-13022-9_63
IEA/AIE (1)
Keywords
Field
DocType
certain knowledge acquisition task,recommender knowledge base,empirical knowledge engineering,constraint-based recommender application,sales rule,constraint-based recommenders,cognitive aspect,knowledge base,product assortment,complex product,knowledge engineer,basic recommendation,recommender knowledge base development,knowledge engineering,empirical study,cognitive psychology,empirical studies,recommender system
Data science,Procedural knowledge,Domain knowledge,Computer science,Knowledge management,Knowledge-based systems,Knowledge value chain,Knowledge engineering,Knowledge base,Empirical research,Knowledge acquisition
Conference
Volume
ISSN
ISBN
6096
0302-9743
3-642-13021-6
Citations 
PageRank 
References 
3
0.42
7
Authors
4
Name
Order
Citations
PageRank
Alexander Felfernig11121110.93
Monika Mandl2828.92
Anton Pum330.42
Monika Schubert4888.64