Job Recommendation: An Approach to Match Job-Seeker’s Interest with Enterprise’s Requirement

Research in Intelligent and Computing in Engineering - Advances in Intelligent Systems and Computing ◽

10.1007/978-981-15-7527-3_35 ◽

2021 ◽

pp. 361-367

Author(s):

Ngoc-Trung-Kien Ho ◽

Hung Ho-Dac ◽

Tuan-Anh Le

Keyword(s):

Job Recommendation

Download Full-text

Implementation K-Means Clustering Method in Job Recommendation System

10.1109/iceeie52663.2021.9616654 ◽

2021 ◽

Author(s):

Betty Dewi Puspasari ◽

Lany Lukita Damayanti ◽

Andy Pramono ◽

Aang Kisnu Darmawan

Keyword(s):

Recommendation System ◽

Clustering Method ◽

Job Recommendation

Download Full-text

Ontology-based job recommendation system with dynamic source updates by slowly changing source detection

International Journal of Knowledge Engineering and Soft Data Paradigms ◽

10.1504/ijkesdp.2016.084595 ◽

2016 ◽

Vol 5 (3/4) ◽

pp. 164

Author(s):

Uma Pavan Kumar Kethavarapu ◽

Selvarajan Saraswathi

Keyword(s):

Recommendation System ◽

Source Detection ◽

Dynamic Source ◽

Job Recommendation

Download Full-text

Machine learned job recommendation

Proceedings of the fifth ACM conference on Recommender systems - RecSys '11 ◽

10.1145/2043932.2043994 ◽

2011 ◽

Cited By ~ 47

Author(s):

Ioannis Paparrizos ◽

B. Barla Cambazoglu ◽

Aristides Gionis

Keyword(s):

Job Recommendation

Download Full-text

Adaptive methods for job recommendation based on user clustering

2016 3rd National Foundation for Science and Technology Development Conference on Information and Computer Science (NICS) ◽

10.1109/nics.2016.7725643 ◽

2016 ◽

Cited By ~ 2

Author(s):

Quoc-Dung Nguyen ◽

Tin Huynh ◽

Tu-Anh Nguyen-Hoang

Keyword(s):

Adaptive Methods ◽

User Clustering ◽

Job Recommendation

Download Full-text

Ontology-based job recommendation system with dynamic source updates by slowly changing source detection

International Journal of Knowledge Engineering and Soft Data Paradigms ◽

10.1504/ijkesdp.2016.10005487 ◽

2016 ◽

Vol 5 (3/4) ◽

pp. 164

Author(s):

Selvarajan Saraswathi ◽

Uma Pavan Kumar Kethavarapu

Keyword(s):

Recommendation System ◽

Source Detection ◽

Dynamic Source ◽

Job Recommendation

Download Full-text

Hybrid deep collaborative filtering for job recommendation

2017 2nd IEEE International Conference on Computational Intelligence and Applications (ICCIA) ◽

10.1109/ciapp.2017.8167222 ◽

2017 ◽

Cited By ~ 2

Author(s):

Weijian Chen ◽

Xingming Zhang ◽

Haoxiang Wang ◽

Hongjie Xu

Keyword(s):

Collaborative Filtering ◽

Job Recommendation

Download Full-text

The analysis and design of the job recommendation model based on GBRT and time factors

2016 IEEE International Conference on Knowledge Engineering and Applications (ICKEA) ◽

10.1109/ickea.2016.7802987 ◽

2016 ◽

Author(s):

Pengyang Wang ◽

Yingtong Dou ◽

Yang Xin

Keyword(s):

Time Factors ◽

Analysis And Design ◽

Model Based ◽

Job Recommendation

Download Full-text

A combination of simple models by forward predictor selection for job recommendation

Proceedings of the Recommender Systems Challenge on - RecSys Challenge '16 ◽

10.1145/2987538.2987548 ◽

2016 ◽

Cited By ~ 3

Author(s):

Dávid Zibriczky

Keyword(s):

Job Recommendation ◽

Selection For ◽

Simple Models

Download Full-text

A bottom-up approach to job recommendation system

Proceedings of the Recommender Systems Challenge on - RecSys Challenge '16 ◽

10.1145/2987538.2987546 ◽

2016 ◽

Cited By ~ 2

Author(s):

Sonu K. Mishra ◽

Manoj Reddy

Keyword(s):

Recommendation System ◽

Bottom Up ◽

Job Recommendation

Download Full-text

Applying Classifications Techniques in Job Recommendation System for Matching of Candidates and Advertisements

International Journal of Intelligent Computing Research ◽

10.20533/ijicr.2042.4655.2017.0098 ◽

2017 ◽

Vol 8 (1) ◽

pp. 798-806 ◽

Cited By ~ 1

Author(s):

Gözde Özcan ◽

Sule Gündüz Ögüdücü

Keyword(s):

Recommendation System ◽

Job Recommendation

Download Full-text