Context-Aware Recommendations for Sustainable Wardrobes

• Published in: Smart Objects and Technologies for Social Good Vol. 233; pp. 51 - 60
• Main Authors: Kolstad, Anders, Özgöbek, Özlem, Gulla, Jon Atle, Litlehamar, Simon
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2018; Springer International Publishing
• Series: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
• Subjects: Bag of concepts; Content-based recommendation; Internet of Things; Linked open data; Recommender systems; Textile recycling
• ISBN: 9783319761107; 3319761102
• ISSN: 1867-8211; 1867-822X
• DOI: 10.1007/978-3-319-76111-4_6

Through recycling textile waste, greenhouse gas emissions can drastically be reduced. Such textile recycling has become a lot easier with clothing retailers now starting to offer recycling checkpoints. Moreover, people today are often challenged by overloaded wardrobes and store many clothing items that they never use. In this paper, we describe an Internet of Things system that creates incentives for the users to recycle their clothes, benefiting the environmental sustainability. We propose a content-based recommendation approach that utilizes semantic web technologies and that leverages a set of context signals obtained from the system’s architecture, to recommend clothing items that might be relevant for the user to recycle. Experiments on a real-world dataset show that our proposed approach outperforms a baseline which does not utilize semantic web technologies.