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Titlebook: von Harnack Kinderheilkunde; Berthold Koletzko Textbook 200011th edition Springer-Verlag Berlin Heidelberg 2000 Infektionskrankheiten.Kind

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B. Koletzkovaluable resource for researchers, practitioners,and students working in information retrieval and databases. Forinstructors, a set of Powerpoint slides, including speaker notes, areavailable online from the authors.978-1-4613-7532-6978-1-4615-5539-1Series ISSN 0893-3405
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E. Harms,B. Koletzko,K. Kruse, the Pre-LN Transformer places the normalization layer in the residual block to make the model more stable. On this basis, we reconstruct the Vader lexicon and further integrate sentiment lexical features extracted from the lexicon into the model. We perform sentiment classification tasks on two pu
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H. P. Schwarz context representation. Finally, the sequence information and syntactic information are fused and mapped to the category feature space through a fully-connected layer. The evaluation on the original ChemProt corpus demonstrates that in comparison to other pre-trained model-based methods, our method
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U. Wahn,V. Wahnion in Begriffshierarchien, die nach den Sachgebieten Regionen, Branchen und Variablen getrennt sind. Ziel ist es, die Mensch-Computer-Schnittstelle so zu gestalten, daß den Nutzern thematische Zusammenhänge näher gebracht und mit dem Navigieren die Formulierung der Suchanfrage nahtlos verbunden wer
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G. Hausdorfems based on the NLPCC2016 Document Based Question Answering (DBQA) corpus. One uses the BM25 model to retrieve the candidate answer sentences, and another uses the Convolution Neural Network (CNN) model. Extracted paraphrases are quite effective in question reformulation, enhancing the MRR from 56.
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