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  1. Farazi, M.: Faceted lightweight ontologies : a formalization and some experiments (2010) 0.02 
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    Content
    PhD Dissertation at International Doctorate School in Information and Communication Technology. Vgl.: https%3A%2F%2Fcore.ac.uk%2Fdownload%2Fpdf%2F150083013.pdf&usg=AOvVaw2n-qisNagpyT0lli_6QbAQ.
  2. Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005) 0.02 
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    Content
    Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.
  3. Xiong, C.: Knowledge based text representations for information retrieval (2016) 0.02 
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    Content
    Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.
  4. Gordon, T.J.; Helmer-Hirschberg, O.: Report on a long-range forecasting study (1964) 0.02 
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    Date
    22. 6.2018 13:24:08
    22. 6.2018 13:54:52
  5. Garfield, E.: ¬An algorithm for translating chemical names to molecular formulas (1961) 0.01 
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    Abstract
    This dissertation discusses, explains, and demonstrates a new algorithm for translating chemica l nomenclature into molecular formulas. In order to place the study in its proper context and perspective the historical development of nomenclature is first discussed, aa well as other related aspects of the chemical information problem. The relationship of nomenclature to modern linguistic studies is then introduced. Tire relevance of structural linguistic procedures to the study of chemical nomenclature is shown. The methods of the linguist are illustrated by examples from chemical discourse. The algorithm is then explained, first for the human translator and then for use by a computer. Flow diagrams for the computer syntactic analysis, dictionary Iook-up routine, and furmula calculation routine are included. The sampling procedure for testing the algorithm is explained and finalIy, conclusions are drawn with respect to the general validity of the method and the dirsction that might be taken for future research. A summary of modern chemical nomenclature practice is appened primarily for use by the reader who is not familiar with chemical nomenclature.
  6. Huo, W.: Automatic multi-word term extraction and its application to Web-page summarization (2012) 0.01 
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    Date
    10. 1.2013 19:22:47
  7. Ziemba, L.: Information retrieval with concept discovery in digital collections for agriculture and natural resources (2011) 0.01 
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  8. Geisriegler, E.: Enriching electronic texts with semantic metadata : a use case for the historical Newspaper Collection ANNO (Austrian Newspapers Online) of the Austrian National Libraryhek (2012) 0.01 
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    Date
    3. 2.2013 18:00:22
  9. Makewita, S.M.: Investigating the generic information-seeking function of organisational decision-makers : perspectives on improving organisational information systems (2002) 0.01 
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    Date
    22. 7.2022 12:16:58
  10. Kiren, T.: ¬A clustering based indexing technique of modularized ontologies for information retrieval (2017) 0.01 
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    Date
    20. 1.2015 18:30:22
  11. Vocht, L. De: Exploring semantic relationships in the Web of Data : Semantische relaties verkennen in data op het web (2017) 0.00 
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