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D-STHARk: Evaluating Dynamic Scheduling of Tasks in Hybrid Simulated Architectures.

, , , , , , , and . ICCS, volume 80 of Procedia Computer Science, page 428-438. Elsevier, (2016)

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Evaluating Different Strategies to Mitigate the Ramp-up Problem in Recommendation Domains., , , , and . WebMedia, page 333-340. ACM, (2017)Mitigating Matching Scarcity in Recruitment Recommendation Domains., , and . WebMedia, page 165-172. ACM, (2020)A Feature-Oriented Sentiment Rating for Mobile App Reviews., , , , , , , and . WWW, page 1909-1918. ACM, (2018)The Oblivion Problem: Exploiting Forgotten Items to Improve Recommendation Diversity., , , and . DiveRS@RecSys, volume 816 of CEUR Workshop Proceedings, page 27-34. CEUR-WS.org, (2011)Offline Evaluation Standards for Recommender Systems., , , , , and . RecSys, page 567-568. ACM, (2021)Hierarchical Density-Based Clustering based on GPU Accelerated Data Indexing Strategy., , , , , , , and . ICCS, volume 80 of Procedia Computer Science, page 951-961. Elsevier, (2016)Reactivity in Online Auctions: Understanding Bidding Behavior through Reactive Transitions., , , , and . CEC/EEE, page 279-284. IEEE Computer Society, (2008)Classificação Automática de Documentos Robusta Temporalmente., , , , , and . SBBD, page 106-119. SBC, (2009)A Particle Swarm approach to mitigate the apparent diversity-accuracy dilemma in recommendation domains in recommendation domains., , , , , and . CEC, page 2183-2190. IEEE, (2019)A characterization methodology for candidates and recruiters interaction in online recruitment services., , and . WebMedia, page 333-340. ACM, (2019)