Searched for:
(1 - 7 of 7)
document
Sun, Zhu (author), Yang, J. (author), Zhang, J. (author), Bozzon, A. (author), Huang, Long Kai (author), Xu, Chi (author)
Knowledge graphs (KGs) have proven to be effective to improve recommendation. Existing methods mainly rely on hand-engineered features from KGs (e.g., meta paths), which requires domain knowledge. This paper presents RKGE, a KG embedding approach that automatically learns semantic representations of both entities and paths between entities...
conference paper 2018
document
Szlávik, Z. (author), Yang, J. (author), Bozzon, A. (author)
Enterprise crowdsourcing capitalises on the availability of employees for in-house data processing. Gamification techniques can help aligning employees' motivation to the crowdsourcing endeavour. Although hitherto, research efforts were able to unravel the wide arsenal of gamification techniques to construct engagement loops, little research has...
conference paper 2018
document
Yang, J. (author), Sun, Zhu (author), Bozzon, A. (author), Zhang, J. (author), Larson, M.A. (author)
The "International Workshop on Recommender Systems for Citizens" (CitRec) is focused on a novel type of recommender systems both in terms of ownership and purpose: recommender systems run by citizens and serving society as a whole.
conference paper 2017
document
Sun, Zhu (author), Yang, J. (author), Zhang, Jie (author), Bozzon, A. (author), Chen, Yu (author), Xu, Chi (author)
Representation learning (RL) has recently proven to be effective in capturing local item relationships by modeling item co-occurrence in individual user's interaction record. However, the value of RL for recommendation has not reached the full potential due to two major drawbacks: 1) recommendation is modeled as a rating prediction problem...
conference paper 2017
document
Yang, J. (author), Cantador, Iván (author), Nurbakova, Diana (author), Cortés-Cediel, María E. (author), Bozzon, A. (author)
This manifesto summarises the outcomes of the 1st Workshop on Recommender Systems for Citizens (CitRec'17), held at the 11th ACM Conference on Recommender Systems, in August 2017 in Como, Italy. We discuss challenges and opportunities for the development of recommender systems for citizens, including: the clarification of the role of recommender...
conference paper 2017
document
Yang, J. (author), Bozzon, A. (author)
Micro-task crowdsourcing has become a successful mean to obtain high-quality data from a large crowd of diverse people. In this context, trust between all the involved actors (i.e. requesters, workers, and platform owners) is a critical factor for acceptance and long-term success. As actors have no expectation for “real life” meetings, thus...
conference paper 2016
document
Yang, J. (author), Hauff, C. (author), Bozzon, A. (author), Houben, G.J.P.M. (author)
Collaborative Question Answering (cQA) platforms are a very popular repository of crowd-generated knowledge. By formulating questions, users express needs that other members of the cQA community try to collaboratively satisfy. Poorly formulated questions are less likely to receive useful responses, thus hindering the overall knowledge generation...
conference paper 2014
Searched for:
(1 - 7 of 7)