Research Papers On Computer Science

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CSO currently powers several tools adopted by the Springer Nature editorial team and has been used to enable a variety of solutions, such as classifying research publications, detecting research communities, and predicting research trends.

As an effort to encourage the usage of CSO, we have developed the CSO Portal, a web application that enables users to download, explore, and provide granular feedbacks at different levels of the ontology.

Due to licenses we cannot always host the papers themselves (when we do, you will see a emoji next to its title in the directory README) but we can provide links to their locations.

If you enjoy the papers, perhaps stop by a local chapter meetup and join in on the vibrant discussions around them.BSc(Tech) students must complete COMPX101 or ENGEN103, COMPX102, COMPX201, COMPX202, COMPX203, COMPX204, COMPX301 or COMPX361 and at least 15 points from List B.To complete Computer Science as part of a double major for the BCMS(Hons), BSc or other undergraduate degree, students must gain 120 points from papers listed for Computer Science, including 90 points above 100 level, and 30 points above 200 level.BCMS(Hons) and BSc students must complete COMPX101 or ENGEN103, COMPX102, COMPX201, COMPX202, COMPX203, COMPX204, COMPX361 and at least 15 points from List B.Students in the BCMS(Hons) will also need to take at least 60 points in the subject of Computer Science at 500 level, including COMPX520.When starting a chapter, please review our guidelines and ask us about using the logo.Computer Science is available as a major for the Bachelor of Computing and Mathematical Sciences with Honours, the Bachelor of Science, and the Bachelor of Science (Technology).These details should be considered as only a guide to the number of downloads performed manually.Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.However, the hottest topics are broad and intentionally defined with some vagueness, to encourage out-of-the-box thinking.For such topics, zooming in on the right questions often marks significant progress in itself. Abundant-data applications, algorithms, and architectures are a meta-topic that includes research avenues such as data mining (quickly finding relatively simple patterns in massive amounts of loosely structured data, evaluating and labeling data, etc), machine learning (building mathematical models that represent structure and statistical trends in data, with good predictive properties), hardware architectures to process more data than is possible today.

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