Scientific publications play a vital role in the career of a researcher. However, some articles become more popular than others among the research community and subsequently drive future research directions. One of the indicative signs of popular articles is the number of citations an article receives. The citation count, which is also the basis with various other metrics, such as the journal impact factor score, the $h$-index, is an essential measure for assessing a scientific paper's quality. In this work, we proposed a Graph Convolutional Network (GCN) based framework for estimating future research publication citations for both the short-term (1-year) and long-term (for 5-years and 10-years) duration. We have tested our proposed approach over the AMiner dataset, specifically on research articles from the computer science domain, consisting of more than 0.8 million articles.

The explosion of user-generated content (UGC)--e.g. social media posts, comments, and reviews--has motivated the development of NLP applications tailored to these types of informal texts. Prevalent among these applications have been sentiment analysis and machine translation (MT). Grounded in the observation that UGC features highly idiomatic, sentiment-charged language, we propose a decoder-side approach that incorporates automatic sentiment scoring into the MT candidate selection process. We train separate English and Spanish sentiment classifiers, then, using n-best candidates generated by a baseline MT model with beam search, select the candidate that minimizes the absolute difference between the sentiment score of the source sentence and that of the translation, and perform a human evaluation to assess the produced translations. Unlike previous work, we select this minimally divergent translation by considering the sentiment scores of the source sentence and translation on a continuous interval, rather than using e.g. binary classification, allowing for more fine-grained selection of translation candidates. The results of human evaluations show that, in comparison to the open-source MT baseline model on top of which our sentiment-based pipeline is built, our pipeline produces more accurate translations of colloquial, sentiment-heavy source texts.

Arriving a symbolic and symmetric 27 years after he died at the age of 27, a "new" Nirvana song has been released. What makes "Drowned In The Sun" very different to "'You Know You're Right" – the last track Nirvana recorded in 1994 but which was not released until 2002 – is that Kurt Cobain did not write it and no members of Nirvana played on it. The track in question was created using artificial intelligence (AI) software that analyzed a number of Nirvana tracks in order to mimic their writing, recording and lyrical styles – drawing on vocals by Eric Hogan, lead singer in Nevermind, a Nirvana tribute act. Such digital necromancy comes with a whole host of moral, ethical and musical concerns, but in this case it is part of the Lost Tapes Of The 27 Club project raising awareness of mental health issues in music. The 27 Club refers to that mythologized grouping of musicians who all died at the age of 27.

From writer-director Neil Burger ("Divergent") comes another young adult science-fiction tale, this one of a cruise ship in deep space full of restless teenagers under the supervision of a single adult. Some of the young people find out that the adult is keeping them drugged and docile and forcing them to reproduce artificially. Is that a recipe for YA trouble or what? Just when you thought you could not watch one more film of this kind, here is "Voyagers," a title that sounds enough like "Passengers" (2016) to put you off you spaceship-grown peas and carrots. The story is set in 2063 when Earth is ravaged, and scientists have searched for another planet to colonize.

… advantages the Defense Department would receive by applying machine learning and artificial intelligence to all-domain information, Air Force Gen.

Yesterday (5th) marked the twenty-seventh anniversary of Nirvana frontman/guitarist Kurt Cobain's death. He was twenty-seven years old. A project called Lost Tapes of the 27 Club released the "new" Nirvana song titled "Drowned In The Sun." One could assume the song was released after discovering old recordings. However, the track was written by Artificial Intelligence and was released to raise awareness of mental health issues in the music industry.

Increasingly we use machine learning to build interactive systems that learn from past actions and the reward obtained. Theory suggests several possible approaches, such as contextual bandits, reinforcement learning, the do-calculus, or plain old Bayesian decision theory. What are the most theoretically appropriate and practical approaches to doing causal inference for interactive systems? We are particularly interested in case studies of applying machine learning methods to interactive systems that did or did not use Bayesian or likelihood based methods, with a discussion about why this choice was made in terms of practical or theoretical arguments.

I need to retrieve data for Machine Learning training using sample data from event sites for training of a web scraper. Are you sure this is what you want to do? A web scraper is typically rule-based (e.g. But to answer your question, Amazon Mechanical Turk is by far the largest platform if you want to access (mostly unskilled) workforce, as long as you can frame your task into a questionnaire (i.e.

The second session tackles the advanced AI techniques required to optimize retail inventory and pick-and-pack operations.

ARLINGTON, Va. — The Navy is very much on board for integrating artificial intelligence (AI) and machine learning into its networks, but human …