Temat: data stream - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Extensible event stream format for navigational data
Autorzy:: Dramski, M.
Powiązania:: https://bibliotekanauki.pl/articles/135232.pdf
Data publikacji:: 2016
Wydawca:: Akademia Morska w Szczecinie. Wydawnictwo AMSz
Tematy:: eXtensible Event Stream
XES standard
process mining
navigational data
data mining
modeling
XML
Opis:: The eXtensible Event Stream (XES) format is a new approach to illustrate the process data. Every ship journey is a sequence of some activities which can be read using different sources of data such ARPA, AIS etc. So we can say that this is a kind of process and its data can be organized in ordered and simple form. The most popular data formats to show the process data were of course XML and CSV. Currently, we can observe huge progress in the domain of process mining. Every year, new tools appeared and the need for some data standard became necessary. This standard is called Extensible Event Stream. In this paper, the use of XES format in navigational data is described.
Źródło:: Zeszyty Naukowe Akademii Morskiej w Szczecinie; 2016, 47 (119); 61-65
1733-8670
2392-0378
Pojawia się w:: Zeszyty Naukowe Akademii Morskiej w Szczecinie
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Solving Support Vector Machine with Many Examples
Autorzy:: Białoń, P.
Powiązania:: https://bibliotekanauki.pl/articles/308497.pdf
Data publikacji:: 2010
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: concept drift
convex optimization
data mining
network failure detection
stream processing
support vector machines
Opis:: Various methods of dealing with linear support vector machine (SVM) problems with a large number of examples are presented and compared. The author believes that some interesting conclusions from this critical analysis applies to many new optimization problems and indicates in which direction the science of optimization will branch in the future. This direction is driven by the automatic collection of large data to be analyzed, and is most visible in telecommunications. A stream SVM approach is proposed, in which the data substantially exceeds the available fast random access memory (RAM) due to a large number of examples. Formally, the use of RAM is constant in the number of examples (though usually it depends on the dimensionality of the examples space). It builds an inexact polynomial model of the problem. Another author's approach is exact. It also uses a constant amount of RAM but also auxiliary disk files, that can be long but are smartly accessed. This approach bases on the cutting plane method, similarly as Joachims' method (which, however, relies on early finishing the optimization).
Źródło:: Journal of Telecommunications and Information Technology; 2010, 3; 65-70
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

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