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Learning Translation-Based Knowledge Graph Embeddings by N-Pair Translation Loss
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In: Applied Sciences ; Volume 10 ; Issue 11 (2020)
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Aspect-Based Sentiment Analysis Using Aspect Map
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In: Applied Sciences ; Volume 9 ; Issue 16 (2019)
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Abstractive Sentence Compression with Event Attention
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In: Applied Sciences ; Volume 9 ; Issue 19 (2019)
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A Multitask-Based Neural Machine Translation Model with Part-of-Speech Tags Integration for Arabic Dialects
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In: Applied Sciences ; Volume 8 ; Issue 12 (2018)
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A Sentence-To-Sentence Relation Network For Recognizing Textual Entailment ...
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A Sentence-To-Sentence Relation Network For Recognizing Textual Entailment ...
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Target Concept Selection By Property Overlap In Ontology Population ...
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Target Concept Selection By Property Overlap In Ontology Population ...
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Abstract:
An ontology is widely used in many kinds of applications as a knowledge representation tool for domain knowledge. However, even though an ontology schema is well prepared by domain experts, it is tedious and cost-intensive to add instances into the ontology. The most confident and trust-worthy way to add instances into the ontology is to gather instances from tables in the related Web pages. In automatic populating of instances, the primary task is to find the most proper concept among all possible concepts within the ontology for a given table. This paper proposes a novel method for this problem by defining the similarity between the table and the concept using the overlap of their properties. According to a series of experiments, the proposed method achieves 76.98% of accuracy. This implies that the proposed method is a plausible way for automatic ontology population from Web tables. ... : {"references": ["J. Barrasa, O' . Corcho, and A. Go'mez-Pe'rez, \"R2O, an Extensible\nand Semantically Based Database-to-Ontology Mapping Language,\" In\nProceedings of the 2nd Workshop on Semantic Web and Databases,\n2004.", "A. Budanitsky and G. Hirst, \"Evaluating WordNet-based Measures of\nSemantic Distance,\" Computational Linguistics, Vol. 32, No. 1, pp. 13-\n47, 2006.", "S. Castano, S. Espinosa, A. Ferrara, V. Karkaletsis, A. Kaya, S. Melzer,\nR. M\u252c\u00bfoller, S. Montanelli, and G. Petasis, \"Ontology Dynamics with\nMultimedia Information: The BOEMIE Evolution Methodology,\" In\nProceedings of International Workshop on Ontology Dynamics, 2007.", "H. Davulcu, S. Vadrevu, S. Nagarajan, and I.V. Ramakrishnan, \"OntoMiner:\nBootstrapping and Populating Ontologies from Domain-\nSpecific Web Sites,\" IEEE Intelligent Systems, Vol. 18, No. 5, pp. 24-33,\n2003.", "S. Handschuh, R. Volz, and S. Staab, \"Annotating for the Deep Web,\"\nIEEE Intelligent Systems, Vol. 18, No. 5, pp. 42-48, 2003.", "J. Jiang ...
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Keyword:
domain knowledge consolidation; Ontology population; property overlap.; target concept selection
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URL: https://zenodo.org/record/1060660 https://dx.doi.org/10.5281/zenodo.1060660
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Determining The Gender Of Korean Names For Pronoun Generation ...
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Determining The Gender Of Korean Names For Pronoun Generation ...
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Resolving Dependency Ambiguity Of Subordinate Clauses Using Support Vector Machines ...
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Resolving Dependency Ambiguity Of Subordinate Clauses Using Support Vector Machines ...
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Ontology Kernel - A Convolution Kernel for Ontology Alignment
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In: http://journal.iis.sinica.edu.tw/paper/1/130648-3.pdf?cd%3D4FDE03273B6C6DD40
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Korean Compound Noun Decomposition Using Syllabic Information Only
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In: http://scai.snu.ac.kr/~scai/Publications/Journals/International/LNCS_2945_143-154(2004).pdf
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Semantic Role Determination in Korean Relative Clauses Using Idiomatic Patterns
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In: http://nova.snu.ac.kr/~sbpark/PostScript/iccpol97.ps
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Determining the Gender of Korean Names for Pronoun Generation
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In: http://www.waset.org/journals/waset/v32/v32-9.pdf
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English-Korean Machine Transliteration by Combining Statistical Model and Web Search
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In: http://www.iaeng.org/publication/IMECS2011/IMECS2011_pp15-20.pdf
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