TY - GEN
T1 - Similarity measure based on hierarchical pair-wise sequence
AU - Sun, Quan
AU - He, Nengqiang
AU - Xu, Lei
AU - Li, Yipeng
AU - Ren, Yong
PY - 2012
Y1 - 2012
N2 - Collaborative filtering systems have achieved great success in both research and business applications. One of the key technologies in collaborative filtering is similarity measure. Cosine-based and Pearson correlation-based methods are popular ways for similarity measure, but have low accuracy. In this paper, we propose a novel method for similarity measure, referred as hierarchical pair-wise sequence (HPWS). In HPWS, we take into account both the sequence property of user behaviors and the hierarchical property of item categories. We design a collaborative filtering recommendation system to evaluate the performance of HPWS based on the empirical data collected from a real P2P application, i.e. byrBT in CERNET. Experiment results show that HPWS outperforms traditional Cosine similarity and Pearson similarity measures under all scenarios.
AB - Collaborative filtering systems have achieved great success in both research and business applications. One of the key technologies in collaborative filtering is similarity measure. Cosine-based and Pearson correlation-based methods are popular ways for similarity measure, but have low accuracy. In this paper, we propose a novel method for similarity measure, referred as hierarchical pair-wise sequence (HPWS). In HPWS, we take into account both the sequence property of user behaviors and the hierarchical property of item categories. We design a collaborative filtering recommendation system to evaluate the performance of HPWS based on the empirical data collected from a real P2P application, i.e. byrBT in CERNET. Experiment results show that HPWS outperforms traditional Cosine similarity and Pearson similarity measures under all scenarios.
KW - Collaborative Filtering
KW - Hierarchical Graph
KW - Sequence Matching
KW - Similarity Measure
UR - http://www.scopus.com/inward/record.url?scp=84861066836&partnerID=8YFLogxK
U2 - 10.1109/ICCSEE.2012.69
DO - 10.1109/ICCSEE.2012.69
M3 - Conference contribution
AN - SCOPUS:84861066836
SN - 9780769546476
T3 - Proceedings - 2012 International Conference on Computer Science and Electronics Engineering, ICCSEE 2012
SP - 512
EP - 516
BT - Proceedings - 2012 International Conference on Computer Science and Electronics Engineering, ICCSEE 2012
T2 - 2012 International Conference on Computer Science and Electronics Engineering, ICCSEE 2012
Y2 - 23 March 2012 through 25 March 2012
ER -