Towards a scalable social recommender engine for online marketplaces: the case of apache solr
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Summary
The details of a social recommender engine for online marketplaces built upon the well-known search engine Apache Solr are presented and the architecture and implementation details are described to facilitate the re-use of the approach by people implementing recommender systems.
- Type
- article
- Published
- 2014-04-07
- Cited by
- 27
- References
- 27
- OpenAlex
- https://openalex.org/W41608943
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:831408
Keywords
Computer science, Recommender system, Scalability, Exploit, Benchmarking
References
- Relational databases versus information retrieval systems: A case study
- Predicting purchase behaviors from social media
- Hybrid Recommender Systems: Survey and Experiments
- An open architecture for collaborative filtering of netnews
- An online recommendation system for e-commerce based on apache mahout framework
- MyMediaLite: a free recommender system library
- Evaluating collaborative filtering recommender systems
- Selecting content-based features for collaborative filtering recommenders
- Real-time top-n recommendation in social streams
- A RecDB in Action: Recommendation Made Easy in Relational Databases
- User-Based Collaborative-Filtering Recommendation Algorithms on Hadoop
- Item-based collaborative filtering recommendation algorithms
- Fab: content-based, collaborative recommendation
- Being accurate is not enough: how accuracy metrics have hurt recommender systems
- Matrix Factorization Techniques for Recommender Systems
- TasteWeights: a visual interactive hybrid recommender system
- Improving Collaborative Filtering in Social Tagging Systems for the Recommendation of Scientific Articles
- Using graph partitioning techniques for neighbour selection in user-based collaborative filtering
- An analysis of tag-recommender evaluation procedures
- GroupLens
Cited by
- Utilizing Online Social Network and Location-Based Data to Recommend Items in an Online Marketplace
- SocRecM: a scalable social recommender engine for online marketplaces
- Smart booking without looking: providing hotel recommendations in the TripRebel portal
- Index partitioning through a bipartite graph model for faster similarity search in recommendation systems
- A Distributed Recommendation Platform for Big Data
- "Real-time recommendations in a multi-domain environment" by Emanuel Lacic with Prateek Jain as coordinator
- Modeling Activation Processes in Human Memory to Improve Tag Recommendations
- Shopping Decisions Made in a Virtual World: Defining a State-Based Model of Collaborative and Conversational User-Recommender Interactions
- ScaR: Towards a Real-Time Recommender Framework Following the Microservices Architecture
- Implementing Big Data Lake for Heterogeneous Data Sources
- Using the Open Meta Kaggle Dataset to Evaluate Tripartite Recommendations in Data Markets
- Should we embed? A study on the online performance of utilizing embeddings for real-time job recommendations
- Microblogs data management: a survey
- A Recommender System to Help Discovering Cohorts in Rare Diseases
- Recommendations in a Multi-Domain Setting: Adapting for Customization, Scalability and Real-Time Performance
- Uptrendz: API-Centric Real-time Recommendations in Multi-Domain Settings
- A Study on Accuracy, Miscalibration, and Popularity Bias in Recommendations
- Knowledge Graph-based Recommendation Engine: The Review
- Generative AI-Powered Spark Cluster Recommendation Engine
- Enhanced Spark Cluster Recommendation Engine Powered by Generative AI
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