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Akademický článek

Are Stock Markets Driven More by Sentiments than Efficiency?

Autor: Miroslawa Lasek, Jan Lasek

Publikováno v: Journal of Engineering, Project, and Production Management, Vol 6, Iss 1, Pp 53-62 (2016)

In this paper, we investigate whether the sentiment contained in text of news items influences a company’s stock price. With the means of sentiment analysis, a quantitative approach for measuring sentiment in text, we derive scores for positive and

Externí odkaz: https://doaj.org/article/e60f43be834445b488d283110d8ab8a0

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Interpretable sports team rating models based on the gradient descent algorithm

Autor: Marek Gagolewski, Jan Lasek

Publikováno v: International Journal of Forecasting. 37:1061-1071

We introduce several new sports team rating models based on the gradient descent algorithm. More precisely, the models can be formulated by maximising the likelihood of match results observed using a single step of this optimisation heuristic. The pr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::82aae4ced6bd4838dd6876997bfd8bbf
https://doi.org/10.1016/j.ijforecast.2020.11.008

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The efficacy of league formats in ranking teams

Autor: Marek Gagolewski, Jan Lasek

Publikováno v: Statistical Modelling. 18:411-435

The efficacy of different league formats in ranking teams according to their true latent strength is analysed. To this end, a new approach for estimating attacking and defensive strengths based on the Poisson regression for modelling match outcomes i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::fc82e3edbf73eb75d4c462db81398a28
https://doi.org/10.1177/1471082x18798426

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Probabilistic movement models and zones of control

Autor: Sebastian Mair, Jan Lasek, Ulf Brefeld

Publikováno v: Brefeld, U, Lasek, J & Mair, S 2019, ' Probabilistic movement models and zones of control ' Machine Learning, vol 108, no. 1, pp. 127-147 . DOI: 10.1007/s10994-018-5725-1
Brefeld, U, Lasek, J & Mair, S 2019, ' Probabilistic movement models and zones of control ', Machine Learning, vol. 108, no. 1, pp. 127-147 . https://doi.org/10.1007/s10994-018-5725-1

Coordinated movements of players are key to success in team sports. However, traditional models for player movements are based on unrealistic assumptions and their analysis is prone to errors. As a remedy, we propose to estimate individual movement m

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::61703a4657bad612ab1e8ba5a446e335
https://www.scopus.com/record/display.uri?eid=2-s2.0-85049144661&origin=SingleRecordEmailAlert&dgcid=raven_sc_affil_en_us_email&txGid=a1b36c50e8a352731cb1a754c64fb95a

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How to improve a team's position in the FIFA ranking? - A simulation study

Autor: Jan Lasek, Marek Gagolewski, Sandjai Bhulai, Zoltán Szlávik

Publikováno v: Journal of Applied Statistics, 43(7), 1349-1368. Routledge
Lasek, J, Szlavik, Z, Gagolewski, M & Bhulai, S 2016, ' How to improve a team's position in the FIFA ranking?-A simulation study ', Journal of Applied Statistics, vol. 43, no. 7, pp. 1349-1368 . https://doi.org/10.1080/02664763.2015.1100593

In this paper, we study the efficacy of the official ranking for international football teams compiled by FIFA, the body governing football competition around the globe. We present strategies for improving a team's position in the ranking. By combini

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9e7e582c29cd0b677b59b9635f761f84
https://doi.org/10.1080/02664763.2015.1100593

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Early Warning System for Seismic Events in Coal Mines Using Machine Learning

Autor: Michal Tadeusiak, Jan Kanty Milczek, Robert Bogucki, Jan Lasek

Publikováno v: FedCSIS
Annals of computer science and information systems, Vol 8, Pp 213-220 (2016)

This document describes an approach to the problem of predicting dangerous seismic events in active coal mines up to 8 hours in advance. It was developed as a part of the AAIA'16 Data Mining Challenge: Predicting Dangerous Seismic Events in Active Co

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd89cfa6731a5bcff359c9bbd1e32522
http://arxiv.org/abs/1609.06957

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The Winning Solution to the AAIA'15 Data Mining Competition: Tagging Firefighter Activities at a Fire Scene

Autor: Marek Gagolewski, Jan Lasek

Publikováno v: FedCSIS

Multi-sensor based classification of professionals' activities plays a key role in ensuring the success of an his/her goals. In this paper we present the winning solution to the AAIA'15 Tagging Firefighter Activities at a Fire Scene data mining compe

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2e524a814d1b4a96fcdcd20652616234
https://doi.org/10.15439/2015f418

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Learning experts’ preferences from informetric data

Autor: Marek Gagolewski, Jan Lasek

Publikováno v: IFSA-EUSFLAT

In the field of informetrics, agents are often represented by numeric sequences of non necessarily conforming lengths. There are numerous aggregation techniques of such sequences, e.g., the g-index, the h-index, that may be used to compare the output

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::35fec0feef671a8cf86becc616382b53
https://doi.org/10.2991/ifsa-eusflat-15.2015.70

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The Use of Fuzzy Relations in the Assessment of Information Resources Producers’ Performance

Autor: Marek Gagolewski, Jan Lasek

Publikováno v: Advances in Intelligent Systems and Computing ISBN: 9783319113098

The producers assessment problem has many important practical instances: it is an abstract model for intelligent systems evaluating e.g. the quality of computer software repositories, web resources, social networking services, and digital libraries.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6d9de5e1da386fc2de05fd7b7e7bc169
https://doi.org/10.1007/978-3-319-11310-4_25

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