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Integrated territorial investment as instrument for managing transport security in lower Silesia’s largest cities

Glinka K.

Zeszyty Naukowe. Transport / Politechnika Śląska

2017

z. 94

37--46

The main aim of this article is to analyse the role and importance of Integrated Territorial Investment (ITI) as the instrument for the management of transport security in the four largest cities of Lower Silesia: Wrocław, Wałbrzych, Legnica and Jelenia Góra. The doubt concerning the potential connected with using ITI is reasonable in the sense that it creates a completely new, previously unknown, mechanism for the implementation of EU cohesion policy. The conducted analysis, covering the level of strategic management, does not allow for a full confirmation of the formulated hypotheses, for two reasons. Firstly, only three out of the four cities in question (Wrocław, Wałbrzych and Jelenia Góra) use ITI in the management of transport security. Secondly, although the use of ITI complements the assumptions of Poland’s National Urban Policy (NUP), which highlights the importance of strategic programming and a multimodal approach in the management of transport security, the scale of this usage is the same as in the case of those cities with integrated, detailed transport strategies, as well as cities without such strategies.

Effective multi-label classification method with applications to text document categorization

Glinka K., Zakrzewska D.

Information Systems in Management

2016

Vol. 5, No. 1

24--35

Increasing number of repositories of online documents resulted in growing demand for automatic categorization algorithms. However, in many cases the texts should be assigned to more than one class. In the paper, new multi-label classification algorithm for short documents is considered. The presented problem transformation Labels Chain (LC) algorithm is based on relationship between labels, and consecutively uses result labels as new attributes in the following classification process. The method is validated by experiments conducted on several real text datasets of restaurant reviews, with different number of instances, taking into account such classifiers as kNN, Naive Bayes, SVM and C4.5. The obtained results showed the good performance of the LC method, comparing to the problem transformation methods like Binary Relevance and Label Powerset.