Handling cold start problem in Recommender Systems by using Interaction Based Social Proximity factor

2015 ◽  
Author(s):  
Punam Bedi ◽  
Chhavi Sharma ◽  
Pooja Vashisth ◽  
Deepika Goel ◽  
Muskan Dhanda
Keyword(s):  
Recommender Systems ◽  
Cold Start ◽  
Social Proximity ◽  
Cold Start Problem

Facing the cold start problem in recommender systems

2014 ◽  
Vol 41 (4) ◽  
pp. 2065-2073 ◽  
Author(s):  
Blerina Lika ◽  
Kostas Kolomvatsos ◽  
Stathes Hadjiefthymiades
Keyword(s):  
Recommender Systems ◽  
Cold Start ◽  
Cold Start Problem

scholarly journals Semantic Distance Spreading Across Entities in Linked Open Data

Information ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 15
Author(s):  
Sultan Alfarhood ◽  
Susan Gauch ◽  
Kevin Labille
Keyword(s):  
Recommender Systems ◽  
Linked Data ◽  
Open Data ◽  
Cold Start ◽  
Semantic Distance ◽  
Linked Open Data ◽  
Experimental Results ◽  
Distance Calculation ◽  
Cold Start Problem

Recommender systems can utilize Linked Open Data (LOD) to overcome some challenges, such as the item cold start problem, as well as the problem of explaining the recommendation. There are several techniques in exploiting LOD in recommender systems; one approach, called Linked Data Semantic Distance (LDSD), considers nearby resources to be recommended by calculating a semantic distance between resources. The LDSD approach, however, has some drawbacks such as its inability to measure the semantic distance resources that are not directly linked to each other. In this paper, we first propose another variation of the LDSD approach, called wtLDSD, by extending indirect distance calculations to include the effect of multiple links of differing properties within LOD, while prioritizing link properties. Next, we introduce an approach that broadens the coverage of LDSD-based approaches beyond resources that are more than two links apart. Our experimental results show that approaches we propose improve the accuracy of the LOD-based recommendations over our baselines. Furthermore, the results show that the propagation of semantic distance calculation to reflect resources further away in the LOD graph extends the coverage of LOD-based recommender systems.

New technique to alleviate the cold start problem in recommender systems using information from social media and random decision forests

2020 ◽  
Vol 536 ◽  
pp. 156-170 ◽  
Author(s):  
J. Herce-Zelaya ◽  
C. Porcel ◽  
J. Bernabé-Moreno ◽  
A. Tejeda-Lorente ◽  
E. Herrera-Viedma
Keyword(s):  
Social Media ◽  
Recommender Systems ◽  
Cold Start ◽  
New Technique ◽  
Random Decision Forests ◽  
Cold Start Problem

scholarly journals Solving the cold-start problem in recommender systems with social tags

2010 ◽  
Vol 92 (2) ◽  
pp. 28002 ◽  
Author(s):  
Zi-Ke Zhang ◽  
Chuang Liu ◽  
Yi-Cheng Zhang ◽  
Tao Zhou
Keyword(s):  
Recommender Systems ◽  
Cold Start ◽  
Social Tags ◽  
Cold Start Problem
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