Paper Info
Title
Comparative Quantitative Evaluation of Distributed Methods for Explanation Generation and Validation of Floor Plan Recommendations.
Abstract
In this work, we compare different explanation generation and validation methods for semantic search pattern-based retrieval results returned by a case-based framework for support of early conceptual design phases in architecture. Compared methods include two case- and rule-based explanation engines, the third one is the discriminant analysis-based method for explanation and validation prediction and estimation. All of the explanation methods use the same data set for retrieval and subsequent explainability operations for results. We describe the main structure of each method and evaluate their quantitative validation performance against each other. The goal of this work is to examine which method performs better under which circumstances, at which point in time, and how good the potential explanation ant its validation can be predicted in general. To evaluate these issues, we compare not only the general performance, i.e., the average rate of valid explanations but also how the validation rate changes over time using a number of time steps for this comparison. We also show for which search pattern type which methods perform better.
Year
DOI
Venue
2018
10.1007/978-3-030-05453-3_3
ICAART
Field
DocType
Citations 
Data mining,Conceptual design,Architecture,Semantic search,Validation methods,Computer science,Floor plan,Artificial intelligence,Linear discriminant analysis,Case based design,Machine learning
Conference
0
PageRank 
References 
Authors
0.34
6
3
Name
Order
Citations
PageRank
Christian Espinoza-Stapelfeld100.34
Viktor Eisenstadt202.03
Klaus-dieter Althoff3991147.58