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Class association rules with occurrence count in image classification

100%

Kobyliński Ł. , Walczak K.

TASK Quarterly : scientific bulletin of Academic Computer Centre in Gdansk

2007

tom Vol. 11, No 1-2

35-45

The concept of utilizing association rules for classification has emerged in recent years. This approach has often proved to be more efficient and accurate than traditional techniques. In this paper we extend the existing associative classifier building algorithms and apply them to the problem of image classification. We describe a set of photographs with features calculated on the basis of their color and texture characteristics and experiment with different types of rules which use the information about the existence of a particular feature in an image, its occurrence count and spatial proximity to classify the images accurately. We suggest using association rules more closely tied to the nature of the image data and compare the results with those of classification with simpler rules, taking into consideration only the existence of a particular feature on an image.

Korpusomat : a Tool for Creating Searchable Morphosyntactically Tagged Corpora

80%

Kieraś W. , Kobyliński Ł. , Ogrodniczuk M.

Computational Methods in Science and Technology

2018

tom Vol. 24, No. 1

21--27

The paper presents Korpusomat, a web application aimed at building annotated corpora for the purpose of corpus linguistic studies. Korpusomat combines existing tools, such as morphological analyser, tagger and corpus search engine, and provides an easy-to-use environment for building corpora technically compatible with the National Corpus of Polish from almost any text, including texts in binary formats. In the paper we present the current state of the project, its features and functionalities, as well as some future plans and developments tasks. A usage example is also presented.