- freely available
Sensors 2018, 18(7), 2037; https://doi.org/10.3390/s18072037
- A novel LSH variant named converse LSH is developed, which can be utilized to search for the enemy users of a target user, in a time-efficient and privacy-preserving way.
- We utilize converse LSH technique to search for the enemies of a target user and then look for the target user’s similar friends indirectly based on the “enemy’s enemy is a possible friend” inference rule in Social Balance Theory. Afterwards, we generate recommended results by considering the preferences of obtained similar friends, so as to handle the exceptions incurred by recommendation failures.
- Comprehensive experiments are simulated based on Movielens dataset, to test the effectiveness of suggested recommendation approach. Experiment results indicate the advantages of our proposal compared to other competitive approaches when a recommendation failure occurs.
2. Related Work
3. Converse Locality-Sensitive Hashing
4. An Exception Handling Approach Based on Converse LSH
- Step-1: Build user indices offline through traditional LSH technique.
- Step-2: Determine the indirect friends of the target user u* based on user indices and converse LSH technique.
- Step-3: Recommend services to u* based on the possible friends of u*.
5.1. Experiment Configurations
- Random: this benchmark approach predicts the missing service quality data based on the quality of a randomly selected service, and returns the service with the optimal predicted quality.
- WSRec : it predicts the missing service quality data by two pieces of average quality, i.e., average quality of the service rated by all users and average quality of all services rated by the user. Finally, the optimal service is returned to the target user.
- SBT-SR : this approach first looks for the indirect friends of a target user based on Collaborative Filtering and Social Balance Theory, and then recommends appropriate services based on the derived indirect friends.
5.2. Experiment Results
- Profile 1: Accuracy comparison of four approaches
- Profile 2: Efficiency comparison of four approaches
- Profile 3: Accuracy of SerRecconverse-LSH with respect to L and r
- Profile 4: Efficiency of SerRecconverse-LSH with respect to L and r
5.3. Shortcoming Analyses & Future Work
Conflicts of Interest
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