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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 117
Article Submitted : 21307
Article Published : 8476
Total Authors : 22301
Total Reviewer : 802
Total Countries : 156
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| Paper Title: | Skill and Job Recommender System |
| Authors Name: | PRAVEEN K , ABHINAV M , BOOPATHI RAJA I , LAKSHMI KANTH R , MADHAV PRASAD V |
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IJRTI_186652
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| Published Paper Id: | IJRTI2305113 |
| Published In: | Volume 8 Issue 5, May-2023 |
| DOI: | |
| Abstract: | Recommendation is a technique, which provides users with information, which he/she may have been interested in or accessed in the past. Traditional recommender techniques such as content and collaborative filtering are used in various applications such as education, social media, marketing, entertainment, e-governance and many more. Content-based and collaborative filtering have many advantages and disadvantages and they are useful in specific applications. Sparsity and cold start problems are major challenges in content and collaborative filtering respectively. Challenges of content and collaborative filtering can be solved by using hybrid filtering. Hybrid filtering is a combination of the features of two recommender systems like content and collaborative; content based filtering improves the classification accuracy and collaborative model easily gives the best predicted result of a latent factor model. The combination of the two techniques is used to achieve better job and skill recommendations. |
| Keywords: | Content-Based Filtering, Collaborative Filtering, Sparsity, Cold Start, Hybrid Filtering, Latent Factor Model. |
| Cite Article: | "Skill and Job Recommender System", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 5, page no.715 - 722, May-2023, Available :http://www.ijrti.org/papers/IJRTI2305113.pdf |
| Downloads: | 000205374 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2305113
Registration ID:186652
Published In: Volume 8 Issue 5, May-2023
DOI (Digital Object Identifier):
Page No: 715 - 722 Country: Salem, Tamil Nadu, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2305113 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2305113 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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