A case-based reasoning system for interior design using a new cosine similarity retrieval algorithm

During concept design stage, a case-based reasoning (CBR) system is good for searching the most suitable interior design drawing case as a preliminary concept drawing design aid to bridge the design requirements gap between the consigner and the designer. In the case base of the system, features of the pre-stored design drawing cases could be characterized by interval, nominal, ordinal and/or ratio scale data. However, the cosine similarity measure used for case reasoning scarcely deals with mixed measurement scales of interval, nominal, ordinal and ratio scale types. Therefore, the objective of this study has been twofold. The first goal was to propose a new cosine similarity retrieval algorithm for case reasoning, in which mixed measurement scales are considered and applied. The second goal was to propose a CBR system and apply the new cosine similarity retrieval algorithm to the search engine of the CBR system for interior design drawing retrieval. Finally, numerical experiments were carried out to demonstrate the capability and effectiveness of the proposed similarity matching algorithm on the case-based reasoning system.