Universal Algorithm for Trading in Stock Market Based on the Method of Calibration
In this paper, we study the problem of predicting quantity of collaborations in co-authorship network. We formulated our task in terms of link prediction problem on weighted co-authorship network, formed by authors writing papers in co-authorship represented by edges between authors in the network. Our task is formulated as regression for edge weights, for which we use node2vec network embedding and new family of edge embedding operators. We evaluate our model on AMiner co-authorship network and showed that our model of network edge representation has better performance for stated regression link prediction task.
This two-volume set LNCS 10305 and LNCS 10306 constitutes the refereed proceedings of the 15th International Work-Conference on Artificial Neural Networks, IWANN 2019, held at Gran Canaria, Spain, in June 2019. The 150 revised full papers presented in this two-volume set were carefully reviewed and selected from 210 submissions. The papers are organized in topical sections on machine learning in weather observation and forecasting; computational intelligence methods for time series; human activity recognition; new and future tendencies in brain-computer interface systems; random-weights neural networks; pattern recognition; deep learning and natural language processing; software testing and intelligent systems; data-driven intelligent transportation systems; deep learning models in healthcare and biomedicine; deep learning beyond convolution; artificial neural network for biomedical image processing; machine learning in vision and robotics; system identification, process control, and manufacturing; image and signal processing; soft computing; mathematics for neural networks; internet modeling, communication and networking; expert systems; evolutionary and genetic algorithms; advances in computational intelligence; computational biology and bioinformatics.
This volume is the supplementary volume of the 14th International Conference on Formal Concept Analysis (ICFCA 2017), held from June 13th to 16th 2017, at IRISA, Rennes. The ICFCA conference series is one of the major venues for researches from the field of Formal Concept Analysis and related areas to present and discuss their recent work with colleagues from all over the world. Since it has been started in 2003 in Darmstadt, the ICFCA conference series had been held in Europe, Australia, America, and Africa.
The field of Formal Concept Analysis (FCA) originated in the 1980s in Darmstadt as a subfield of mathematical order theory, with prior developments in other research groups. Its original motivation was to consider complete lattices as lattices of concepts, drawing motivation from philosophy and mathematics alike. FCA has since then devel- oped into a wide research area with applications much beyond its original motivation, for example in logic, data mining, learning, and psychology.
The FCA community is mourning the passing of Rudolf Wille on January 22nd 2017 in Bickenbach, Germany. As one of the leading researchers throughout the history of FCA, he was responsible for inventing and shaping many of the fundamental notions of this area. Indeed, the publication of his article ”Restructuring Lattice Theory: An Approach Based on Hierarchies of Concepts” is seen by many as the starting point of Formal Concept Analysis as an independent direction of research. He was head of the FCA research group in Darmstadt from 1983 until his retirement in 2003, and remained an active researcher and contributor thereafter. In 2003, he was among the founding members of the ICFCA conference series.
For this supplementary volume, 13 papers were chosen to be published: four papers judged mature enough to be discussed at the conference and nine papers presented in the demonstration and poster sssion.
В данной работе проводится исследование и разработка метода кластеризации пользователей социальных сетей на группы, на основе описания к кинофильмам.