Catálogo de publicaciones - libros

This research paper presents a parallel immune algorithm, par-IA, using the LAM/MPI library to tackle global numerical optimization problems. par-IA has been compared with two important clonal selection algorithms, CLONALG and opt-IA, and a well-known evolutionary algorithm for function optimization, FEP. The experimental results show a global better performance of par-IA with respect to optIA, CLONALG, and FEP. Considering the results obtained, we can claim that par-IA is a robust immune algorithm for effectively performing global optimization tasks.

Aerial archaeology plays an important role in the detection and documentation of archaeological sites, which often cannot be easily seen from the ground. It is a quick way to survey large areas, but requires a lot of error-prone human work to analyze it afterwards. In this paper we utilize some of the best-performing image processing and data mining methods to develop a system capable of an accurate automated classification of such aerial photographs. The system consists of phases of image indexing, rough image segmentation, feature extraction, feature grouping and building the classifier. We present the results of experiments conducted on a real set of archaeological and non-archaeological aerial photographs and conclude with perspectives for future work.

Aerial archaeology plays an important role in the detection and documentation of archaeological sites, which often cannot be easily seen from the ground. It is a quick way to survey large areas, but requires a lot of error-prone human work to analyze it afterwards. In this paper we utilize some of the best-performing image processing and data mining methods to develop a system capable of an accurate automated classification of such aerial photographs. The system consists of phases of image indexing, rough image segmentation, feature extraction, feature grouping and building the classifier. We present the results of experiments conducted on a real set of archaeological and non-archaeological aerial photographs and conclude with perspectives for future work.

The paper focuses on finding spatial association rules. A new approach to mining spatial association rules is proposed. The neighborhood is defined in terms of the Delaunay diagrams, instead of predefining distance thresholds with extra runs. Once a Delaunay diagram is created, it is used for determining neighborhoods, and then, based on this knowledge it continues with finding association rules.

This paper describes a morphological analyser for Polish. Its features include a large dictionary, a carefully designed tagset, presentation of results as a DAG of interpretations, high efficiency, and free availability for non-commercial use and scientific research.

The paper presents a program for automatic spelling correction of texts from a very specific domain, which has been applied to mammography reports. We describe different types of errors and present the program of correction based on the Levenshtein distance and probability of bigrams.

The paper presents an approach to tagging of Polish based on the combination of handmade reduction rules and selecting rules acquired by Induction of Decision Trees. The general open architecture of the tagger is presented, where the overall process of tagging is divided into subsequent steps and the overall problem is reduced to subproblems of ambiguity classes. A special language of constraints and the use of constraints as elements of decision trees are described. The results of the experiments performed with the tagger are also presented.