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Passing from requirements specification to class model using application domain ontology
PublikacjaThe quality of a classic software engineering process depends on the completeness of project documents and on the inter-phase consistency. In this paper, a method for passing from the requirement specification to the class model is proposed. First, a developer browses the text of the requirements, extracts the word sequences, and places them as terms into the glossary. Next, the internal ontology logic for the glossary needs to...
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Text Categorization Improvement via User Interaction
PublikacjaIn this paper, we propose an approach to improvement of text categorization using interaction with the user. The quality of categorization has been defined in terms of a distribution of objects related to the classes and projected on the self-organizing maps. For the experiments, we use the articles and categories from the subset of Simple Wikipedia. We test three different approaches for text representation. As a baseline we use...
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How Specific Can We Be with k-NN Classifier?
PublikacjaThis paper discusses the possibility of designing a two stage classifier for large-scale hierarchical and multilabel text classification task, that will be a compromise between two common approaches to this task. First of it is called big-bang, where there is only one classifier that aims to do all the job at once. Top-down approach is the second popular option, in which at each node of categories’ hierarchy, there is a flat classifier...
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Selection of Relevant Features for Text Classification with K-NN
PublikacjaIn this paper, we describe five features selection techniques used for a text classification. An information gain, independent significance feature test, chi-squared test, odds ratio test, and frequency filtering have been compared according to the text benchmarks based on Wikipedia. For each method we present the results of classification quality obtained on the test datasets using K-NN based approach. A main advantage of evaluated...
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Improving css-KNN Classification Performance by Shifts in Training Data
PublikacjaThis paper presents a new approach to improve the performance of a css-k-NN classifier for categorization of text documents. The css-k-NN classifier (i.e., a threshold-based variation of a standard k-NN classifier we proposed in [1]) is a lazy-learning instance-based classifier. It does not have parameters associated with features and/or classes of objects, that would be optimized during off-line learning. In this paper we propose...
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Follow the Light. Where to search for useful research information
PublikacjaArchitectural Lighting Design (ALD) has never been a standalone professional discipline. Rather, it has existed as the combination of art and the science of light. Today, third generation lighting professionals are already creatively intertwining these fields, and the acceleration in scientific, technological and societal studies has only increased the need for reliable multidisciplinary information. Therefore, a thorough re-examination...
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Identification of category associations using a multilabel classifier
PublikacjaDescription of the data using categories allows one to describe it on a higher abstraction level. In this way, we can operate on aggregated groups of the information, allowing one to see relationships that do not appear explicit when we analyze the individual objects separately. In this paper we present automatic identification of the associations between categories used for organization of the textual data. As experimental data...