TY - GEN
T1 - Extra
T2 - 12th ACM Conference on Recommender Systems, RecSys 2018
AU - Zhou, Qinghai
AU - Li, Liangyue
AU - Cao, Nan
AU - Buchler, Norbou
AU - Tong, Hanghang
N1 - Publisher Copyright:
© 2018 Copyright held by the owner/author(s).
PY - 2018/9/27
Y1 - 2018/9/27
N2 - State-of-the-art in network science of teams offers effective recommendation methods to answer questions like who is the best replacement, what is the best team expansion strategy, but lacks intuitive ways to explain why the optimization algorithm gives the specific recommendation for a given team optimization scenario. To tackle this problem, we develop an interactive prototype system, Extra, as the first step towards addressing such a sense-making challenge, through the lens of the underlying network where teams embed, to explain the team recommendation results. The main advantages are (1) Algorithm efficacy: we propose an effective and fast algorithm to explain random walk graph kernel, the central technique for networked team recommendation; (2) Intuitive visual explanation: we present intuitive visual analysis of the recommendation results, which can help users better understand the rationality of the underlying team recommendation algorithm.
AB - State-of-the-art in network science of teams offers effective recommendation methods to answer questions like who is the best replacement, what is the best team expansion strategy, but lacks intuitive ways to explain why the optimization algorithm gives the specific recommendation for a given team optimization scenario. To tackle this problem, we develop an interactive prototype system, Extra, as the first step towards addressing such a sense-making challenge, through the lens of the underlying network where teams embed, to explain the team recommendation results. The main advantages are (1) Algorithm efficacy: we propose an effective and fast algorithm to explain random walk graph kernel, the central technique for networked team recommendation; (2) Intuitive visual explanation: we present intuitive visual analysis of the recommendation results, which can help users better understand the rationality of the underlying team recommendation algorithm.
KW - Random Walk Graph Kernel
KW - Team Recommendation Explanation
KW - Visualization
UR - http://www.scopus.com/inward/record.url?scp=85056758868&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85056758868&partnerID=8YFLogxK
U2 - 10.1145/3240323.3241610
DO - 10.1145/3240323.3241610
M3 - Conference contribution
AN - SCOPUS:85056758868
T3 - RecSys 2018 - 12th ACM Conference on Recommender Systems
SP - 492
EP - 493
BT - RecSys 2018 - 12th ACM Conference on Recommender Systems
PB - Association for Computing Machinery
Y2 - 2 October 2018 through 7 October 2018
ER -