Recommendation algorithm
We have collected a variety of datasets that are frequently utilized in the research domain of HashRec. These datasets are essential for conducting comprehensive and insightful studies on hashing-based recommendation systems. For individuals interested in delving deeper into the specifics of these datasets, including their sources, structures, and usage instructions, please refer to the dedicated repository at https://github.com/Luo-Fangyuan/HashRec.
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Building meaningful connections between students and alumni is critical for enhancing students’ professional growth, career advice, and networking. Despite these benefits, traditional platforms often lack personalization and scalability, limiting their ability to meet diverse student needs. This paper presents an AI-driven approach to revolutionize student-alumni interactions wih career guidance by leveraging advanced recommendation systems.
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Over the past few years YouTube has became a popular site for video broadcasting and earning money by publishing various different skills in the form of videos. For some people it has become a main source to earn money. Getting the videos trending among the viewers is one of the major tasks which each and every content creator wants. Popularity of any video and its reach to the audience is completely based on YouTube's Recommendation algorithm. This document is a dataset descriptor for the dataset collected over the time span of about 45 days during the Israel-Hamas War
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