Wyniki wyszukiwania - Biblioteka Nauki

1

Interactive Method for Semantic Document Indexing Based on Explicit Semantic Analysis

100%

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

Fundamenta Informaticae

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2014

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tom 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.

2

The platform for semantic integration and sharing technological knowledge on metal processing and casting

86%

Kluska-Nawarecka S. , Nawarecki E. , Dobrowolski G. , Haratym A. , Regulski K.

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tom Vol. 13, No. 2

304--312

EN

This paper presents the concept of knowledge sharing platform, which uses an ontological model for integration purposes. The platform is expected to serve the needs of the metals processing industry, and its immediate purpose is to build an integrated knowledge base, which will allow the semantic search supported by domain ontology. Semantic search will resolve the difficulties encountered in the class of Information Retrieval Systems associated with polysemy and synonyms, and will make the search for properties (relations), not just the keywords, possible. An open platform model using Semantic Media Wiki in conjunction with the author's script parsing the domain ontology will be presented.

PL

Artykuł prezentuje koncepcję platformy udostępniania wiedzy wykorzystującą w celach integracji model ontologiczny. Platforma ma służyć celom przemysłu przetwórstwa metali: budować zintegrowaną bazę wiedzy, w której możliwe będzie wyszukiwanie semantyczne wspierane przez ontologię dziedzinową. Wyszukiwanie semantyczne pozwoli rozwiązać trudności spotykane w systemach klasy Information Retrieval Systems związane z polisemią i synonimami, a także umożliwi wyszukiwanie pod względem właściwości (relacji), a nie tylko po słowach kluczowych. Przedstawiony zostanie model wykorzystujący otwartą platformę Semantic Media Wiki w połączeniu z autorskim skryptem parsującym ontologię dziedzinową.

3

Usage of deep learning in recent applications

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Dubey A.

Archives of Materials Science and Engineering

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2022

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tom Vol. 115, nr 2

49--57

EN

Purpose: Deep learning is a predominant branch in machine learning, which is inspired by the operation of the human biological brain in processing information and capturing insights. Machine learning evolved to deep learning, which helps to reduce the involvement of an expert. In machine learning, the performance depends on what the expert extracts manner features, but deep neural networks are self-capable for extracting features. Design/methodology/approach: Deep learning performs well with a large amount of data than traditional machine learning algorithms, and also deep neural networks can give better results with different kinds of unstructured data. Findings: Deep learning is an inevitable approach in real-world applications such as computer vision where information from the visual world is extracted, in the field of natural language processing involving analyzing and understanding human languages in its meaningful way, in the medical area for diagnosing and detection, in the forecasting of weather and other natural processes, in field of cybersecurity to provide a continuous functioning for computer systems and network from attack or harm, in field of navigation and so on. Practical implications: Due to these advantages, deep learning algorithms are applied to a variety of complex tasks. With the help of deep learning, the tasks that had been said as unachievable can be solved. Originality/value: This paper describes the brief study of the real-world application problems domain with deep learning solutions.

4

Dynamic semantic description and search methods for heterogeneous learning resources

72%

Lai X. , Pan Y. , Jiang X.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2022

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tom Vol. 70, nr 3

art. no. e139434

EN

Learning resources are massive, heterogeneous, and constantly changing. How to find the required resources quickly and accurately has become a very challenging work in the management and sharing of learning resources. According to the characteristics of learning resources, this paper proposes a progressive learning resource description model, which can describe dynamic heterogeneous resource information on a fine-grained level by using information extraction technology, then a semantic annotation algorithm is defined to calculate the semantic of learning resource and add these semantic to the description model. Moreover, a semantic search method is proposed to find the required resources, which calculate the content with the highest similarity to the user query, and then return the results in descending order of similarity. The simulation results show that the method is feasible and effective.

5

The Use of Formal Knowledge Representation in Operating on Resources Concerning Cast Iron Processing

58%

Kluska-Nawarecka S. , Wilk-Kołodziejczyk D. , Rojek G. , Regulski K. , Polek G.

Archives of Foundry Engineering

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2015

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tom Vol. 15, iss. 2

39--42

EN

The problem of materials selection in terms of their mechanical properties during the design of new products is a key issue of design. The complexity of this process is mainly due to a multitude of variants in the previously produced materials and the possibility of their further processing improving the properties. In everyday practice, the problem is solved basing on expert or designer knowledge. The paper is the proposition of a solution using computer-aided analysis of material experimental data, which may be acquired from external data sources. In both cases, taking into account the rapid growth of data, additional tools become increasingly important, mainly those which offer support for adding, viewing, and simple comparison of different experiments. In this paper, the use of formal knowledge representation in the form of an ontology is proposed as a bridge between physical repositories of data in the form of files and user queries, which are usually formulated in natural language. The number and the sophisticated internal structure of attributes or parameters that could be the criteria of the search for the user are an important issue in the traditional data search tools. Ontology, as a formal representation of knowledge, enables taking into account the known relationships between concepts in the field of cast iron, materials used and processing techniques. This allows the user to receive support by searching the results of experiments that relate to a specific material or processing treatment. Automatic presentation of the results which relate to similar materials or similar processing treatments is also possible, which should make the conducted analysis of the selection of materials or processing treatments more comprehensive by including a wider range of possible solutions.

6

Zmiany w modelach i technologiach informacyjnych w dobie Web 2.0 i Web 3.0

36%

Brzostek-Pawłowska J.

Elektronika : konstrukcje, technologie, zastosowania

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2011

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tom Vol. 52, nr 3

143-151

PL

Pod wpływem dynamicznego rozwoju sieci, serwisów i aplikacji społecznych Web 2.0 intensyfikują się strumienie informacji i powiększają zasoby tworzone społecznie. Zmieniają się modele pozyskiwania, dostarczania i absorpcji wiedzy, jak również potrzeby i oczekiwania użytkowników. W ślad za tymi zjawiskami nadążają technologie informacyjne semantycznego Web 3.0, których zadaniem jest skuteczne i efektywne pokonanie głodu wiedzy. Artykuł przedstawia technologie Web 2.0 i ich wpływ na zmianę modeli pozyskiwania i dostarczania wiedzy realizowanych technologiami Web 3.0, omawia też cechy nowoczesnych systemów informacyjnych w dobie Web 2.0 i Web 3.0 i prezentuje ich przykłady.

EN

The dynamic development of the Web 2.0-of social networks and of social applications has impact on the growth of the social resources and of the streams of information. Models of knowledge acquisition and delivery as well as users' needs and expectations are changing under the influence of Web 2.0. Along with these phenomena are developed and implemented information technologies of semantic Web 3-0, whose task is to effectively overcome the hunger for knowledge and information. The article presents the Web 2.0 technologies and their impact on change in models of knowledge acquisition and delivery implemented with using of Web 3.0 technologies, also have been discussed the characteristics of modem informalion systems in the era of Web 2.0 and Web 3.0, and presented examples.