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CV Retrieval System based on job description matching using hybrid word embeddings

  • Published:2019-07 Issue: Volume:56 Page:73-79
  • ISSN:0885-2308
  • Container-title:Computer Speech & Language
  • language:en
  • Short-container-title:Computer Speech & Language

Author:

Fernández-Reyes Francis C.,Shinde Suraj

Publisher

Elsevier BV

Reference27 articles.

1. Corpus Specificity in LSA and Word2vec: The Role of Out-of-Domain Documents;Altszyler,2018

2. Latent semantic indexing (LSI) fails for trec collections;Atreya;SIGKDD Explor. Newsl.,2011

3. Don’t count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors;Baroni,2014

4. A neural probabilistic language model;Bengio;J. Mach. Learn. Res.,2003

5. Diversifying query auto-completion;Cai;ACM Trans. Inf. Syst.,2016

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1. Ontology and its applications in skills matching in job recruitment;Applied Ontology: An Interdisciplinary Journal of Ontological Analysis and Conceptual Modeling;2024-10-01

2. A Challenge-based Survey of E-recruitment Recommendation Systems;ACM Computing Surveys;2024-06-22

3. Strategic Decision-Making for Pedagogical Course Planning Using NLP in Social Media Data;Advanced Sciences and Technologies for Security Applications;2023

4. Skill Scanner: Connecting and Supporting Employers, Job Seekers and Educational Institutions with an AI-Based Recommendation System;Lecture Notes in Networks and Systems;2022-12-16

5. Towards an Integrated Retrieval System to Semantically Match CVs, Job Descriptions and Curricula;Proceedings of the 26th Pan-Hellenic Conference on Informatics;2022-11-25
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