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Job Recommendations: Benchmarking of Collaborative Filtering Methods for Classifieds
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-0-387-85820-3_8openalex-snapshot
Evaluating Recommendation Systems
inferredcites →https://doi.org/10.1007/978-3-319-29659-3openalex-snapshot
Recommender Systems: The Textbook
inferredcites →https://doi.org/10.1007/978-3-540-72079-9_9openalex-snapshot
Collaborative Filtering Recommender Systems
inferredcites →https://doi.org/10.1007/s11257-020-09269-1openalex-snapshot
Using autoencoders for session-based job recommendations
inferredcites →https://doi.org/10.1016/j.ins.2009.12.010openalex-snapshot
Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power
inferredcites →https://doi.org/10.1016/j.knosys.2017.02.009openalex-snapshot
Diversity in recommender systems – A survey
inferredcites →https://doi.org/10.1080/01621459.1937.10503522openalex-snapshot
The Use of Ranks to Avoid the Assumption of Normality Implicit in the Analysis of Variance
inferredcites →https://doi.org/10.1080/03610928008827904openalex-snapshot
Approximations of the critical region of the fbietkan statistic
inferredcites →https://doi.org/10.1086/376808openalex-snapshot
When More Is Less and Less Is More: The Role of Ideal Point Availability and Assortment in Consumer Choice
inferredcites →https://doi.org/10.1109/access.2018.2877208openalex-snapshot
A Survey of Collaborative Filtering-Based Recommender Systems: From Traditional Methods to Hybrid Methods Based on Social Networks
inferredcites →https://doi.org/10.1109/access.2023.3249356openalex-snapshot
Comparison of Real-Time and Batch Job Recommendations
inferredcites →https://doi.org/10.1109/icdm.2008.22openalex-snapshot
Collaborative Filtering for Implicit Feedback Datasets
inferredcites →https://doi.org/10.1109/icdm.2011.134openalex-snapshot
SLIM: Sparse Linear Methods for Top-N Recommender Systems
inferredcites →https://doi.org/10.1109/mc.2009.263openalex-snapshot
Matrix Factorization Techniques for Recommender Systems
inferredcites →https://doi.org/10.1109/mic.2017.72openalex-snapshot
Two Decades of Recommender Systems at Amazon.com
inferredcites →https://doi.org/10.1109/mlsp.2016.7738886openalex-snapshot
ITEM2VEC: Neural item embedding for collaborative filtering
inferredcites →https://doi.org/10.1145/1869446.1869453openalex-snapshot
Comparison of implicit and explicit feedback from an online music recommendation service
inferredcites →https://doi.org/10.1145/2043932.2043987openalex-snapshot
Applications of the conjugate gradient method for implicit feedback collaborative filtering
inferredcites →https://doi.org/10.1145/2507157.2507210openalex-snapshot
Learning to rank recommendations with the k-order statistic loss
inferredcites →https://doi.org/10.1145/2567948.2579244openalex-snapshot
Random walks in recommender systems
inferredcites →https://doi.org/10.1145/2926720openalex-snapshot
Diversity, Serendipity, Novelty, and Coverage
inferredcites →https://doi.org/10.1145/2955101openalex-snapshot
Updatable, Accurate, Diverse, and Scalable Recommendations for Interactive Applications
inferredcites →https://doi.org/10.1145/2959100.2959162openalex-snapshot
Modelling Contextual Information in Session-Aware Recommender Systems with Neural Networks
inferredcites →https://doi.org/10.1145/3298689.3347032openalex-snapshot
Predicting online performance of job recommender systems with offline evaluation
inferredcites →https://doi.org/10.1145/3331184.3331267openalex-snapshot
Neural Graph Collaborative Filtering
inferredcites →https://doi.org/10.1145/3383313.3418479openalex-snapshot
Exploring Data Splitting Strategies for the Evaluation of Recommendation Models
inferredcites →https://doi.org/10.1145/3397271.3401403openalex-snapshot
Deep Job Understanding at LinkedIn
inferredcites →https://doi.org/10.1145/3434185openalex-snapshot
A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research
inferredcites →https://doi.org/10.1145/3460231.3478848openalex-snapshot
Quality Metrics in Recommender Systems: Do We Calculate Metrics Consistently?
inferredcites →https://doi.org/10.1145/3503252.3531292openalex-snapshot
Top-N Recommendation Algorithms: A Quest for the State-of-the-Art
inferredcites →https://doi.org/10.1145/3539618.3591785openalex-snapshot
When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback?
inferredcites →https://doi.org/10.1145/3604915.3609489openalex-snapshot
Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven Analysis
inferredcites →https://doi.org/10.1214/aoms/1177731944openalex-snapshot
A Comparison of Alternative Tests of Significance for the Problem of $m$ Rankings
inferredcites →https://doi.org/10.1287/mksc.1040.0109openalex-snapshot
Overchoice and Assortment Type: When and Why Variety Backfires
inferredcites →https://doi.org/10.13140/2.1.2393.1847openalex-snapshot
Software Framework for Topic Modelling with Large Corpora
inferredcites →https://doi.org/10.1509/jmkg.65.3.50.18330openalex-snapshot
Reducing Assortment: An Attribute-Based Approach
inferredcites →https://doi.org/10.15439/2022f191openalex-snapshot
Learning edge importance in bipartite graph-based recommendations
inferredcites →https://doi.org/10.17705/1jais.00389openalex-snapshot
Online Recommendation Systems in a B2C E-Commerce Context: A Review and Future Directions
inferredcites →https://doi.org/10.2307/3001968openalex-snapshot
Individual Comparisons by Ranking Methods
inferredcites →https://doi.org/10.3390/su14127439openalex-snapshot
Graph-Community-Enabled Personalized Course-Job Recommendations with Cross-Domain Data Integration
inferredcites →https://doi.org/10.48550/arxiv.1310.4546openalex-snapshot
Distributed Representations of Words and Phrases and their Compositionality
inferredcites →https://doi.org/10.5121/mlaij.2016.3103openalex-snapshot
A Survey on Similarity Measures in Text Mining
inferredcites →https://doi.org/10.5897/ijps12.482openalex-snapshot
A survey of job recommender systems
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1016/j.array.2026.100740openalex-snapshot
Segment-Aware LorentzFM: Hyperbolic embedding approach for personalized job recommendations
inferred← citeshttps://doi.org/10.1038/s41598-025-08931-1openalex-snapshot
A transformer-based architecture for collaborative filtering modeling in personalized recommender systems
inferred← citeshttps://doi.org/10.1063/5.0299300openalex-snapshot
Methods and challenges in job recommendation systems: A review
inferred← citeshttps://doi.org/10.1109/access.2023.3249356openalex-snapshot
Comparison of Real-Time and Batch Job Recommendations
inferred← citeshttps://doi.org/10.1109/iciscois62701.2026.11447695openalex-snapshot
SmartBlend: A Hybrid Filtering Framework for Intelligent Recommendation Systems
inferred← citeshttps://doi.org/10.1109/iiceta57613.2023.10351342openalex-snapshot
Avoidance of Scalability Problem in Recommendation System Using Filtering Approch
inferred← citeshttps://doi.org/10.1109/sist61657.2025.11139304openalex-snapshot
Intelligent Career Path Recommendations Leveraging Blockchain and Machine Learning
inferred← citeshttps://doi.org/10.1109/ubmk67458.2025.11206977openalex-snapshot
The Optimal Action Set: Evidence-Based Design Principles for Job Search Platforms
inferred← citeshttps://doi.org/10.23939/acps2025.01.047openalex-snapshot
Collaborative filtering algorithms for a job recommendation system built with a microservice architecture
inferred← citeshttps://doi.org/10.2478/amns-2024-3241openalex-snapshot
Personalized Recommendation Mechanism of College English Writing Teaching Content Based on OBE Concept in Big Data Environment
inferred← citeshttps://doi.org/10.3390/jimaging11010012openalex-snapshot
Hybrid Quality-Based Recommender Systems: A Systematic Literature Review
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