Rs4rs: Semantically Find Recent Publications from Top Recommendation System-Related Venues

Fuente: arXiv
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Hauptverfasser: Wijaya, Tri Kurniawan, D'Amico, Edoardo, Fodor, Gabor, Loureiro, Manuel V.
Format: Preprint
Veröffentlicht: 2024
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author Wijaya, Tri Kurniawan
D'Amico, Edoardo
Fodor, Gabor
Loureiro, Manuel V.
author_facet Wijaya, Tri Kurniawan
D'Amico, Edoardo
Fodor, Gabor
Loureiro, Manuel V.
contents Rs4rs is a web application designed to perform semantic search on recent papers from top conferences and journals related to Recommender Systems. Current scholarly search engine tools like Google Scholar, Semantic Scholar, and ResearchGate often yield broad results that fail to target the most relevant high-quality publications. Moreover, manually visiting individual conference and journal websites is a time-consuming process that primarily supports only syntactic searches. Rs4rs addresses these issues by providing a user-friendly platform where researchers can input their topic of interest and receive a list of recent, relevant papers from top Recommender Systems venues. Utilizing semantic search techniques, Rs4rs ensures that the search results are not only precise and relevant but also comprehensive, capturing papers regardless of variations in wording. This tool significantly enhances research efficiency and accuracy, thereby benefitting the research community and public by facilitating access to high-quality, pertinent academic resources in the field of Recommender Systems. Rs4rs is available at https://rs4rs.com.
format Preprint
id arxiv_https___arxiv_org_abs_2409_05570
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Rs4rs: Semantically Find Recent Publications from Top Recommendation System-Related Venues
Wijaya, Tri Kurniawan
D'Amico, Edoardo
Fodor, Gabor
Loureiro, Manuel V.
Information Retrieval
Rs4rs is a web application designed to perform semantic search on recent papers from top conferences and journals related to Recommender Systems. Current scholarly search engine tools like Google Scholar, Semantic Scholar, and ResearchGate often yield broad results that fail to target the most relevant high-quality publications. Moreover, manually visiting individual conference and journal websites is a time-consuming process that primarily supports only syntactic searches. Rs4rs addresses these issues by providing a user-friendly platform where researchers can input their topic of interest and receive a list of recent, relevant papers from top Recommender Systems venues. Utilizing semantic search techniques, Rs4rs ensures that the search results are not only precise and relevant but also comprehensive, capturing papers regardless of variations in wording. This tool significantly enhances research efficiency and accuracy, thereby benefitting the research community and public by facilitating access to high-quality, pertinent academic resources in the field of Recommender Systems. Rs4rs is available at https://rs4rs.com.
title Rs4rs: Semantically Find Recent Publications from Top Recommendation System-Related Venues
topic Information Retrieval
url https://arxiv.org/abs/2409.05570