48 Citations
Optimizing Online Social Networks for Information Propagation
- Computer SciencePloS one
- 2014
This paper designs a new similarity measure which takes into account users' activity frequencies and finds that previous social recommendation methods lead to serious delay of information propagation since many users are connected to inactive leaders.
Membership in social networks and the application in information filtering
- Computer ScienceArXiv
- 2013
It is found that the users who have collected only a few objects are more likely to be “influenced” by the membership when choosing objects, and a social diffusion recommendation algorithm is designed which can effectively solve the user cold-start problem.
Personalized recommendation via an improved NBI algorithm and user influence model in a Microblog network
- Computer Science
- 2013
Recommendation of Leaders in Online Social Systems
- Computer ScienceISMIS
- 2012
The simulation results on real networks show that the proposed leader recommendation method can accurately recommend the potential leaders and further investigation on recommendation diversity indicates that the recommendation method is very personalized.
Adaptive social recommendation in a multiple category landscape
- Computer ScienceArXiv
- 2012
This work introduces a more realistic assumption that users’ tastes are modeled by multiple vectors, and designs novel measures of users�’ taste similarity that can substantially improve the precision of the recommender system.
Extracting the Information Backbone in Online System
- Computer SciencePloS one
- 2013
This paper designs some algorithms to improve the recommendation performance by eliminating some links from the original networks and proposes a hybrid method combining the time-aware and topology-aware link removal algorithms to extract the backbone which contains the essential information for the recommender systems.
Evaluating user reputation in online rating systems via an iterative group-based ranking method
- Computer ScienceArXiv
- 2015
References
SHOWING 1-10 OF 104 REFERENCES
Empirical analysis of web-based user-object bipartite networks
- Computer ScienceArXiv
- 2009
This letter reports the empirical analysis on two large-scale web sites, audioscrobbler.com and del.icio.us, and proposes a new index, named collaborative similarity, to quantify the diversity of tastes based on the collaborative selection.
Effects of high-order correlations on personalized recommendations for bipartite networks
- Computer Science
- 2010
Effect of user tastes on personalized recommendation
- Computer ScienceArXiv
- 2009
The effects of user tastes on the mass-diffusion-based personalized recommendation algorithm, where a user's tastes or interests are defined by the average degree of the objects he has collected, are studied and it is argued that the initial recommendation power located on the objects should be determined by both of their degree and the user's taste.
CAN DISSIMILAR USERS CONTRIBUTE TO ACCURACY AND DIVERSITY OF PERSONALIZED RECOMMENDATION
- Computer Science
- 2010
This paper proposes a recommendation algorithm by considering both the effects of similar and dissimilar users under the framework of collaborative filtering, and shows that it performs much better than the standard collaborative filtering algorithm for both accuracy and diversity.
Information filtering via preferential diffusion
- Computer SciencePhysical review. E, Statistical, nonlinear, and soft matter physics
- 2011
A recommendation algorithm based on the preferential diffusion process on a user-object bipartite network that can not only provide more accurate recommendations, but also generate more diverse and novel recommendations by accurately recommending unpopular objects.
Why Does Collaborative Filtering Work? Transaction-Based Recommendation Model Validation and Selection by Analyzing Bipartite Random Graphs
- Computer ScienceINFORMS J. Comput.
- 2011
This paper develops initial understanding of the recommendation model/algorithm validation and selection issues based on the graph topological modeling methodology and demonstrates the effectiveness of the proposed bipartitegraph topological measures in selection and validation of commonly used heuristic-based recommendation algorithms, the user-based, item- based, and graph-based algorithms.
Spontaneous emergence of social influence in online systems
- Computer ScienceProceedings of the National Academy of Sciences
- 2010
It is demonstrated that even when external signals are absent, social influence can spontaneously assume an on–off nature in a digital environment.
The reinforcing influence of recommendations on global diversification
- Computer Science
- 2012
Simulating successive recommendations and measuring their influence on the dispersion of item popularity by Gini coefficient indicates that local diffusion and collaborative filtering reinforce the popularity of hot items, widening the popularity dispersion, and suggests that recommender systems have reinforcing influence on global diversification.
Solving the Cold-Start Problem in Recommender Systems with Social Tags
- Computer ScienceArXiv
- 2010
Community structure in social and biological networks
- Computer ScienceProceedings of the National Academy of Sciences of the United States of America
- 2002
This article proposes a method for detecting communities, built around the idea of using centrality indices to find community boundaries, and tests it on computer-generated and real-world graphs whose community structure is already known and finds that the method detects this known structure with high sensitivity and reliability.