Semantic Analysis of Soccer News for Automatic Game EventClassification
Nordskog, Aanund Jupskaas; Halvorsen, Pål; Hicks, Steven; Stensland, Haakon; Hammer, Hugo Lewi; Johansen, Dag; Riegler, Michael
Conference object
Accepted version
Permanent lenke
https://hdl.handle.net/10642/8508Utgivelsesdato
2019-10-21Metadata
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Originalversjon
Nordskog, Halvorsen P, Hicks S, Stensland, Hammer HL, Johansen D, Riegler M: Semantic Analysis of Soccer News for Automatic Game EventClassification. In: Gurrin CG, Jónsson BT, Peteri R. Proceedings of Content Based Multimedia Information (CBMI 2019), 2019. IEEE conference proceedings https://dx.doi.org/10.1109/CBMI.2019.8877417Sammendrag
We are today overwhelmed with information, of which an important part is news. Sports news, in particular, has become very popular, where soccer makes up a big part of this coverage. For sports fans, it can be a time consuming and tedious to keep up with the news that they really care about. In this paper, we present different machine learning methods applied to soccer news from a Norwegian newspaper and a TV station's news site to summarize the content in a short and digestible manner. We present a system to collect, index, label, analyze, and present the collected news articles based on the content. We perform a thorough comparison between deep learning and traditional machine learning algorithms on text classification. Furthermore, we present a dataset of soccer news which was collected from two different Norwegian news sites and shared online.