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@inproceedings{1359885, author = {Vaculík, Karel}, address = {Bratislava}, booktitle = {Proceedings in Informatics and Information Technologies. Bratislava: WIKT & DaZ}, editor = {Mária Bieliková, Ivan Srba}, keywords = {graph mining; network analysis; data mining; classification; anomaly detection; community detection; recommendation}, howpublished = {tištěná verze "print"}, language = {cze}, location = {Bratislava}, isbn = {978-80-227-4619-9}, pages = {31-34}, publisher = {Nakladatel’stvo STU}, title = {Graph Mining: Applications (invited talk)}, year = {2016} }
TY - JOUR ID - 1359885 AU - Vaculík, Karel PY - 2016 TI - Graph Mining: Applications (invited talk) PB - Nakladatel’stvo STU CY - Bratislava SN - 9788022746199 KW - graph mining KW - network analysis KW - data mining KW - classification KW - anomaly detection KW - community detection KW - recommendation N2 - Traditional data mining algorithms typically assume data instances to be independent. However, there is a lot of real-world scenarios where relationships between data instances exist and they are principal for data understanding. For example, there are relationships between people in social networks, between chemical elements in chemical compounds, etc. It is difficult or even impossible to express such information in the classical attribute-value representation. Graph mining is an area of data mining that uses a graph representation of data and it allows us to exploit the relationships in the data. The goal of this talk is to present diverse successful applications of graph mining on real-world graphs. ER -
VACULÍK, Karel. Graph Mining: Applications (invited talk). In Mária Bieliková, Ivan Srba. \textit{Proceedings in Informatics and Information Technologies. Bratislava: WIKT \&{} DaZ}. Bratislava: Nakladatel’stvo STU, 2016, s.~31-34. ISBN~978-80-227-4619-9.
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