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    Wyświetlanie 1-6 z 6
    Tytuł:
    Distributed web-scale infrastructure for crawling, indexing and search with semantic support
    Autorzy:
    Dlugolinsky, S.
    Seleng, M.
    Laclavik, M.
    Hluchy, L.
    Powiązania:
    https://bibliotekanauki.pl/articles/305377.pdf
    Data publikacji:
    2012
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    distributed web crawling
    information extraction
    information retrieval
    semantic search
    geocoding
    spatial search
    Opis:
    In this paper, we describe our work in progress in the scope of web-scale information extraction and information retrieval utilizing distributed computing. We present a distributed architecture built on top of the MapReduce paradigm for information retrieval, information processing and intelligent search supported by spatial capabilities. Proposed architecture is focused on crawling documents in several different formats, information extraction, lightweight semantic annotation of the extracted information, indexing of extracted information and finally on indexing of documents based on the geo-spatial information found in a document. We demonstrate the architecture on two use cases, where the first is search in job offers retrieved from the LinkedIn portal and the second is search in BBC news feeds and discuss several problems we had to face during the implemen-tation. We also discuss spatial search applications for both cases because both LinkedIn job offer pages and BBC news feeds contain a lot of spatial information to extract and process.
    Źródło:
    Computer Science; 2012, 13 (4); 5-19
    1508-2806
    2300-7036
    Pojawia się w:
    Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Dynamic semantic description and search methods for heterogeneous learning resources
    Autorzy:
    Lai, Xiaocong
    Pan, Ying
    Jiang, Xueling
    Powiązania:
    https://bibliotekanauki.pl/articles/2173685.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    heterogeneous data
    learning resources
    semantic description
    semantic search
    dane niejednorodne
    zasoby edukacyjne
    opis semantyczny
    wyszukiwanie semantyczne
    Opis:
    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.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 3; art. no. e139434
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Usage of deep learning in recent applications
    Autorzy:
    Dubey, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/24200557.pdf
    Data publikacji:
    2022
    Wydawca:
    Stowarzyszenie Komputerowej Nauki o Materiałach i Inżynierii Powierzchni w Gliwicach
    Tematy:
    conceptual based information retrieval
    ontology
    semantic search
    wyszukiwanie informacji oparte na pojęciach
    ontologia
    wyszukiwanie semantyczne
    Opis:
    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.
    Źródło:
    Archives of Materials Science and Engineering; 2022, 115, 2; 49--57
    1897-2764
    Pojawia się w:
    Archives of Materials Science and Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Computer Catalog and Semantic Search of Data in the Domain of Cast Iron Processing
    Autorzy:
    Rojek, G.
    Regulski, K.
    Wilk-Kołodziejczyk, D.
    Kluska-Nawarecka, S.
    Wawrzaszek, T.
    Powiązania:
    https://bibliotekanauki.pl/articles/381770.pdf
    Data publikacji:
    2017
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    application of information technologies
    foundry
    semantic search
    ontology
    cast iron processing
    zastosowanie technologii informacyjnych
    odlewnictwo
    obróbka żeliwa
    Opis:
    The aim of this study is to design and implement a computer system, which will allow the semantic cataloging and data retrieval in the field of cast iron processing. The intention is to let the system architecture allow for consideration of data on various processing techniques based on the information available or searched by a potential user. This is achieved by separating the system code from the knowledge of the processing operations or from the chemical composition of the material being processed. This is made possible by the creation and subsequent use of formal knowledge representation in the form of ontology. So, any use of the system is associated with the use of ontologies, either as an aid for the cataloging of new data, or as an indication of restrictions imposed on the data which draw user attention. The use of formal knowledge representation also allows consideration of semantic meaning, a consequence of which may be, for example, returning all elements in subclasses of the searched process class or material grade.
    Źródło:
    Archives of Foundry Engineering; 2017, 17, 2; 79-84
    1897-3310
    2299-2944
    Pojawia się w:
    Archives of Foundry Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The Use of Formal Knowledge Representation in Operating on Resources Concerning Cast Iron Processing
    Autorzy:
    Kluska-Nawarecka, S.
    Wilk-Kołodziejczyk, D.
    Rojek, G.
    Regulski, K.
    Polek, G.
    Powiązania:
    https://bibliotekanauki.pl/articles/380345.pdf
    Data publikacji:
    2015
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    information technology
    foundry industry
    automation in foundry
    robotics in foundry
    semantic analysis
    semantic search
    technologia informatyczna
    przemysł odlewniczy
    automatyka w odlewnictwie
    robotyka w odlewnictwie
    analiza semantyczna
    wyszukiwarka semantyczna
    Opis:
    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.
    Źródło:
    Archives of Foundry Engineering; 2015, 15, 2; 39-42
    1897-3310
    2299-2944
    Pojawia się w:
    Archives of Foundry Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A Semantic Framework for Graph-Based Enterprise Search
    Autorzy:
    Modoni, G. E.
    Sacco, M.
    Terkaj, W.
    Powiązania:
    https://bibliotekanauki.pl/articles/118193.pdf
    Data publikacji:
    2014
    Wydawca:
    Polskie Towarzystwo Promocji Wiedzy
    Tematy:
    Enterprise Search
    Graph Knowledge
    semantic web
    Opis:
    Various recent studies have shown that in many companies workers can spend near half of their time looking for information. Effective internal search tools could make their job more efficient. However, a killer application for this type of solutions is still not available. This paper introduces an envisioned architecture, which should represent the foundations of a new generation of tools for searching information within enterprises.
    Źródło:
    Applied Computer Science; 2014, 10, 4; 66-74
    1895-3735
    Pojawia się w:
    Applied Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-6 z 6

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