Top 5 Trending Computer Science Papers in January 2019

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Top 5 Trending Computer Science Papers in January 2019

During January we analysed millions of open access academic papers in Computer Science to discover the top 5 articles being read by Mendeley users in the Computer Science discipline. We believe these papers will have an impact on the influential academic papers of tomorrow.

Mendeley Trending considers the number of people reading a specific paper, the change in number of new readers within a timeframe and how recently the paper was published.

Some of these papers can be viewed on the Mendeley Web Catalog, and to access others you may need to click on ‘Get full text’ to view it on the publisher’s site.


A) A survey on sentiment analysis challenges (230 Readers)

graph of sentiment analysis

With accelerated evolution of the internet as websites, social networks, blogs, online portals, reviews, opinions, recommendations, ratings, and feedback are generated by writers. This writer generated sentiment content can be about books, people, hotels, products, research, events, etc. These sentiments become very beneficial for businesses, governments, and individuals. While this content is meant to be useful, a bulk of this writer generated content require using the text mining techniques an…

Doaa Mohey El Din Mohamed Hussein et al. in Journal of King Saud University – Engineering Sciences (2018)

B) Opportunities and challenges in developing deep learning models using electronic health records data: A systematic review (162 Readers)

Infographics of the opportunities and challenges in developing deep learning models using electronic health data

OBJECTIVE Electronic health records (EHRs) are an increasingly common data source for clinical risk prediction, presenting both unique analytic opportunities and challenges. We sought to evaluate the current state of EHR based risk prediction modeling through a systematic review of clinical prediction studies using EHR data. METHODS We searched PubMed for articles that reported on the use of an EHR to develop a risk prediction model from 2009 to 2014. Articles were extracted by two reviewers, an…

Cao Xiao et al. in Journal of the American Medical Informatics Association (2018)

C) Big Data in Smart Farming – A review (971 Readers)

Smart Farming is a development that emphasizes the use of information and communication technology in the cyber-physical farm management cycle. New technologies such as the Internet of Things and Cloud Computing are expected to leverage this development and introduce more robots and artificial intelligence in farming. This is encompassed by the phenomenon of Big Data, massive volumes of data with a wide variety that can be captured, analysed and used for decision-making. This review aims to gain…

Sjaak Wolfert et al. in Agricultural Systems (2017)

D) Scientific development of smart farming technologies and their application in Brazil (170 Readers)

graphs of scientific development of smart farming technologies

Smart farming (SF) involves the incorporation of information and communication technologies into machinery, equipment, and sensors for use in agricultural production systems. New technologies such as the internet of things and cloud computing are expected to advance this development, introducing more robots and artificial intelligence into farming. Therefore, the aims of this paper are twofold: (i) to characterize the scientific knowledge about SF that is available in the worldwide scientific li…

Dieisson Pivoto et al. in Information Processing in Agriculture (2018)

E) Hierarchical Attention Networks for Document Classification (1349 Readers)

graphs of hierarchical attention networks

We propose a hierarchical attention network for document classification. Our model has two distinctive characteristics: (i) it has a hierarchical structure that mirrors the hierarchical structure of documents; (ii) it has two levels of attention mechanisms applied at the word and sentence-level, enabling it to attend differentially to more and less important content when constructing the document representation. Experiments conducted on six large scale text classification tasks demonstrate that …

Zichao Yang et al. in Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2016)


That’s it for open access Computer Science papers this month. If you enjoyed this post, please let us know with a like or share.

Explore the Mendeley Web Catalog here.

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