首页|New Machine Learning Research from Taif University Discussed (FutureCite: Predic ting Research Articles’ Impact Using Machine Learning and Text and Graph Mining Techniques)
New Machine Learning Research from Taif University Discussed (FutureCite: Predic ting Research Articles’ Impact Using Machine Learning and Text and Graph Mining Techniques)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on artificial in telligence have been published. According to news reporting from Taif University by NewsRx journalists, research stated, “The growth in academic and scientific publications has increased very rapidly. Researchers must choose a representativ e and significant literature for their research, which has become challenging wo rldwide.” The news reporters obtained a quote from the research from Taif University: “Usu ally, the paper citation number indicates this paper’s potential influence and i mportance. However, this standard metric of citation numbers is not suitable to assess the popularity and significance of recently published papers. To address this challenge, this study presents an effective prediction method called Future Cite to predict the future citation level of research articles. FutureCite integ rates machine learning with text and graph mining techniques, leveraging their a bilities in classification, datasets in-depth analysis, and feature extraction. FutureCite aims to predict future citation levels of research articles applying a multilabel classification approach. FutureCite can extract significant semanti c features and capture the interconnection relationships found in scientific art icles during feature extraction using textual content, citation networks, and me tadata as feature resources. This study’s objective is to contribute to the adva ncement of effective approaches impacting the citation counts in scientific publ ications by enhancing the precision of future citations. We conducted several ex periments using a comprehensive publication dataset to evaluate our method and d etermine the impact of using a variety of machine learning algorithms.”
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