Tootfinder

Since it came up in another thread I thought I'd post a link to About Face, an anti-war, anti-cop veterans organization.
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We are Post-9/11 service members and veterans organizing to end a foreign policy of permanent war and the use of military weapons, tactics, and values in communities across the country. As people intimately familiar with the inner workings of the world’s largest military, we use our knowledge and experiences to expose the truth about these conflicts ov…

This https://arxiv.org/abs/2206.02631 has been replaced.
link: https://scholar.google.com/scholar?q=a

Contemporary Recommendation Systems on Big Data and Their Applications: A Survey
This survey paper conducts a comprehensive analysis of the evolution and contemporary landscape of recommendation systems, which have been extensively incorporated across a myriad of web applications. It delves into the progression of personalized recommendation methodologies tailored for online products or services, organizing the array of recommendation techniques into four main categories: content-based, collaborative filtering, knowledge-based, and hybrid approaches, each designed to cater …

This https://arxiv.org/abs/2206.02631 has been replaced.
link: https://scholar.google.com/scholar?q=a

Contemporary Recommendation Systems on Big Data and Their Applications: A Survey
This survey paper conducts a comprehensive analysis of the evolution and contemporary landscape of recommendation systems, which have been extensively incorporated across a myriad of web applications. It delves into the progression of personalized recommendation methodologies tailored for online products or services, organizing the array of recommendation techniques into four main categories: content-based, collaborative filtering, knowledge-based, and hybrid approaches, each designed to cater …

This https://arxiv.org/abs/2206.02631 has been replaced.
link: https://scholar.google.com/scholar?q=a

Contemporary Recommendation Systems on Big Data and Their Applications: A Survey
This survey paper conducts a comprehensive analysis of the evolution and contemporary landscape of recommendation systems, which have been extensively incorporated across a myriad of web applications. It delves into the progression of personalized recommendation methodologies tailored for online products or services, organizing the array of recommendation techniques into four main categories: content-based, collaborative filtering, knowledge-based, and hybrid approaches, each designed to cater …