TY - CHAP

T1 - Propagating Maximum Capacities for Recommendation

AU - Boubekki, Ahcène

AU - Brefeld, Ulf

AU - Lucchesi, Cláudio Leonardo

AU - Stille, Wolfgang

N1 - Conference code: 40

PY - 2017

Y1 - 2017

N2 - Neighborhood-based approaches often fail in sparse scenarios; a direct implication for recommender systems exploiting co-occurring items is often an inappropriately poor performance. As a remedy, we propose to propagate information (e.g., similarities) across the item graph to leverage sparse data. Instead of processing only directly connected items (e.g. co-occurrences), the similarity of two items is defined as the maximum capacity path interconnecting them. Our approach resembles a generalization of neighborhood-based methods that are obtained as special cases when restricting path lengths to one. We present two efficient online computation schemes and report on empirical results.

AB - Neighborhood-based approaches often fail in sparse scenarios; a direct implication for recommender systems exploiting co-occurring items is often an inappropriately poor performance. As a remedy, we propose to propagate information (e.g., similarities) across the item graph to leverage sparse data. Instead of processing only directly connected items (e.g. co-occurrences), the similarity of two items is defined as the maximum capacity path interconnecting them. Our approach resembles a generalization of neighborhood-based methods that are obtained as special cases when restricting path lengths to one. We present two efficient online computation schemes and report on empirical results.

KW - Business informatics

KW - Recommender systems

KW - Maximum capacity paths

KW - Information propagation

KW - Sparsity

KW - Co-occurrence

KW - Cold-start problem

UR - http://www.scopus.com/inward/record.url?scp=85030871909&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-67190-1_6

DO - 10.1007/978-3-319-67190-1_6

M3 - Article in conference proceedings

AN - SCOPUS:85030871909

SN - 978-3-319-67189-5

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 72

EP - 84

BT - KI 2017: Advances in Artificial Intelligence

PB - Springer

CY - Cham, Schweiz

T2 - 40th German Conference on Artificial Intelligence - KI 2017

Y2 - 25 September 2017 through 29 September 2017

ER -