Research papers of computer science

Theory 567 ment 116 and modeling 207 buted systems el computing 202 ics and electronic tion 29 e 141 architecture 64 -computer visualization 408 ation retrieval and the igence 874 tion 400 ation 47 l language processing ty, privacy and tion 278 ering 91 s 273 sing 241 ncy 45 we recently announced our $10001 binary battle to promote applications built on the mendeley api (now including plos as well), i decided to take a look at the data to see what people have to work with. Biological sciences (my discipline) is the largest, but i started with this one so that i could look at the data with fresh eyes, and also because it’s got some really cool papers to talk about. Here’s what i found:What i found was a fascinating list of topics, with many of the expected fundamental papers like shannon’s theory of information and the google paper, a strong showing from mapreduce and machine learning, but also some interesting hints that augmented reality may be becoming more of an actual reality top graph summarizes the overall results of the analysis. This graph shows the top 10 papers among those who have listed computer science as their discipline and chosen a subdiscipline. In fact, ai researchers contributed the majority of readership to 6 out of the top 10 papers.

Research papers for computer science

Presumably, those interested in popular topics such as machine learning list themselves under ai, which explains the strength of this subdiscipline, whereas papers like the mapreduce one or the google paper appeal to a broad range of subdisciplines, giving those papers a smaller numbers spread across more subdisciplines. The importance of the monolithic “big iron” supercomputer has been on the wane for decades. The interesting thing about this paper is that had some of the lowest readership scores of the top papers within a subdiscipline, but folks from across the entire spectrum of computer science are reading it. I would expect that the largest share of readers have it in their library mostly out of curiosity rather than direct relevance to their research. Among ai and information retrieval researchers, this paper discusses recommendation algorithms and classifies them into collaborative, content-based, or hybrid.

I would really have expected this to be at least number 3 or 4, but the strong showing by the ai discipline for the machine learning papers in spots 1, 4, and 5 pushed it down. It’s one of the more fundamental papers of computer science, founding the field of information theory and enabling the development of the very tubes through which you received this web page you’re reading now. This is different from the other papers above in that it’s a descriptive piece, not primary research as above, but still deserves it’s place in the list and readership will only grow as we get ever closer to his vision. While this seems like a highly specialized niche area, it’s of importance to machine learning and ai researchers, so it was able to pull in a nice readership on mendeley. Videos of techniques at scivee or jove or recorded lectures (previously) can really help spread awareness of your research.

Looking across subdisciplines as we did here, it’s not surprising to see two related papers, of interest to the main driving discipline, appear twice. First of all, it shows that mendeley readership data is good enough to reveal both papers of long-standing importance as well as interesting upcoming trends. Comparing yourself against others in terms of readers per paper could put a big smile on your face, or it could be a gentle nudge to get out to more conferences or maybe record a video of your technique for jove or khan academy or just r thing to note is that these results don’t necessarily mean that ai researchers are the most influential researchers or the most numerous, just the best at being accounted for. Split computer vision, robotics and machine learning from ai, since the latest is a fuzzy and uncertain concept. Neural networks could be combined with machine learning, ally in fast-growing fields like computer science, discipline will always be a somewhat fuzzy concept.

We are working on a way for people to assign themselves and papers to disciplines in a more flexible ble for windows, mac osx and our users are sayingmy tweets recent ey & e-pic event in austria on november 21st and november  to work for a top science employer? Introduction to applying for a nih r series for researchers: october webinars in french and german. Sjr uses a similar algorithm as the google page rank; it provides a quantitative and a qualitative measure of the journal’s example article on lides are short, 5-minute presentations in which the author explains their paper in their own in brief authors co-submit and publish a data article in data in brief, it appears on sciencedirect linked to the original research article in this ctive plot example article on application lets readers explore data and other quantitative results submitted with the article, providing insights into and access to data that is otherwise buried in sx authors co-submit and publish a method article in methodsx, it appears on sciencedirect linked to the original research article in this hing your article with us has many benefits, such as having access to a personal dashboard: citation and usage data on your publications in one place. This free service is available to anyone who has published and whose publication is in computer science review ly published articles from computer science review. Terizing ddos attacks and flash events: review, research gaps and future behal | krishan kumar | monika annotated bibliography on n g.

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