Wyniki wyszukiwania - BazTech

1

Modern instruments for occupational safety promotion

Gornostai Oryslava, Menshikova Olga, Stanislavchuk Oksana, Slobodianyk Nadiia

Zeszyty Naukowe Wyższej Szkoły Zarządzania Ochroną Pracy w Katowicach

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2021

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Nr 1(17)

85--90

EN

In today’s world, the knowledge of employees of the enterprise or company is its strategic resource, so the process of knowledge management and maintaining their relevance is becoming increasingly important. The quarantine restrictions imposed by the Covid-19 pandemic necessitated the transfer of vocational and safety training to an online format in search of methods that would bring it as close as possible to the offline format.

PL

W dzisiejszym świecie wiedza pracowników przedsiębiorstwa czy firmy jest jego strategicznym zasobem, dlatego proces zarządzania wiedzą i utrzymywania jej aktualności nabiera coraz większego znaczenia. Ograniczenia kwarantannowe nałożone przez pandemię Covid-19 wymusiły przeniesienie szkoleń zawodowych i BHP do formatu online w poszukiwaniu metod, które zbliżyłyby je jak najbardziej do warunków formatu offline.

2

Unsupervised and Interactive Semi-supervised Clustering for Large Image Database Indexing and Retrieval

Lai H. P., Visani M., Boucher A., Ogier J. M.

Fundamenta Informaticae

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2014

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Vol. 130, nr 2

201--218

EN

The feature space structuring methods play a very important role in finding information in large image databases. They organize indexed images in order to facilitate, accelerate and improve the results of further retrieval. Clustering, one kind of feature space structuring, may organize the dataset into groups of similar objects without prior knowledge (unsupervised clustering) or with a limited amount of prior knowledge (semi-supervised clustering). In this paper, we present both formal and experimental comparisons of different unsupervised clustering methods for structuring large image databases. We use different image databases of increasing sizes (Wang, PascalVoc2006, Caltech101, Corel30k) to study the scalability of the different approaches. Then, we present a new interactive semi-supervised clustering model, which allows users to provide feedback in order to improve the clustering results according to their wishes. Moreover,we also compare, experimentally, our proposed model with the semi-supervised HMRF-kmeans clustering method.

3

Interactive Method for Semantic Document Indexing Based on Explicit Semantic Analysis

Świeboda W., Krasuski A., Nguyen H. S., Janusz A.

Fundamenta Informaticae

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2014

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Vol. 132, nr 3

423--438

EN

In this article we propose a general framework incorporating semantic indexing and search of texts within scientific document repositories. In our approach, a semantic interpreter, which can be seen as a tool for automatic tagging of textual data, is interactively updated based on feedback from the users, in order to improve quality of the tags that it produces. In our experiments, we index our document corpus using the Explicit Semantic Analysis (ESA) method. In this algorithm, an external knowledge base is used to measure relatedness between words and concepts, and those assessments are utilized to assign meaningful concepts to given texts. In the paper, we explain how the weights expressing relations between particular words and concepts can be improved by interaction with users or by employment of expert knowledge. We also present some results of experiments on a document corpus acquired from the PubMed Central repository to show feasibility of our approach.