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Zeng, Q.; Yu, M.; Yu, W.; Xiong, J.; Shi, Y.; Jiang, M.: Faceted hierarchy : a new graph type to organize scientific concepts and a construction method (2019)
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- Content
- Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
-
Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005)
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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.
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Tzitzikas, Y.; Spyratos, N.; Constantopoulos, P.; Analyti, A.: Extended faceted ontologies (2002)
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Yu, L.-C.; Wu, C.-H.; Chang, R.-Y.; Liu, C.-H.; Hovy, E.H.: Annotation and verification of sense pools in OntoNotes (2010)
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- Abstract
- The paper describes the OntoNotes, a multilingual (English, Chinese and Arabic) corpus with large-scale semantic annotations, including predicate-argument structure, word senses, ontology linking, and coreference. The underlying semantic model of OntoNotes involves word senses that are grouped into so-called sense pools, i.e., sets of near-synonymous senses of words. Such information is useful for many applications, including query expansion for information retrieval (IR) systems, (near-)duplicate detection for text summarization systems, and alternative word selection for writing support systems. Although a sense pool provides a set of near-synonymous senses of words, there is still no knowledge about whether two words in a pool are interchangeable in practical use. Therefore, this paper devises an unsupervised algorithm that incorporates Google n-grams and a statistical test to determine whether a word in a pool can be substituted by other words in the same pool. The n-gram features are used to measure the degree of context mismatch for a substitution. The statistical test is then applied to determine whether the substitution is adequate based on the degree of mismatch. The proposed method is compared with a supervised method, namely Linear Discriminant Analysis (LDA). Experimental results show that the proposed unsupervised method can achieve comparable performance with the supervised method.
-
OWL Web Ontology Language Test Cases (2004)
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- Date
- 14. 8.2011 13:33:22
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- n
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Cao, N.; Sun, J.; Lin, Y.-R.; Gotz, D.; Liu, S.; Qu, H.: FacetAtlas : Multifaceted visualization for rich text corpora (2010)
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Monireh, E.; Sarker, M.K.; Bianchi, F.; Hitzler, P.; Doran, D.; Xie, N.: Reasoning over RDF knowledge bases using deep learning (2018)
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- Date
- 16.11.2018 14:22:01
-
ISO/IEC FCD 13250: Topic maps. Information technology (1999)
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Dextre Clarke, S.G.; Will, L.D.; Cochard, N.: ¬The BS8723 thesaurus data model and exchange format, and its relationship to SKOS (2008)
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-
Wang, Y.; Tai, Y.; Yang, Y.: Determination of semantic types of tags in social tagging systems (2018)
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Xiong, C.: Knowledge based text representations for information retrieval (2016)
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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.
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Wang, H.; Liu, Q.; Penin, T.; Fu, L.; Zhang, L.; Tran, T.; Yu, Y.; Pan, Y.: Semplore: a scalable IR approach to search the Web of Data (2009)
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Xu, Y.; Li, G.; Mou, L.; Lu, Y.: Learning non-taxonomic relations on demand for ontology extension (2014)
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Zhang, L.; Liu, Q.L.; Zhang, J.; Wang, H.F.; Pan, Y.; Yu, Y.: Semplore: an IR approach to scalable hybrid query of Semantic Web data (2007)
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Thomer, A.; Cheng, Y.-Y.; Schneider, J.; Twidale, M.; Ludäscher, B.: Logic-based schema alignment for natural history Mmuseum databases (2017)
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Xu, G.; Cao, Y.; Ren, Y.; Li, X.; Feng, Z.: Network security situation awareness based on semantic ontology and user-defined rules for Internet of Things (2017)
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Shen, M.; Liu, D.-R.; Huang, Y.-S.: Extracting semantic relations to enrich domain ontologies (2012)
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Pepper, S.; Arnaud, P.J.L.: Absolutely PHAB : toward a general model of associative relations (2020)
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- Abstract
- There have been many attempts at classifying the semantic modification relations (R) of N + N compounds but this work has not led to the acceptance of a definitive scheme, so that devising a reusable classification is a worthwhile aim. The scope of this undertaking is extended to other binominal lexemes, i.e. units that contain two thing-morphemes without explicitly stating R, like prepositional units, N + relational adjective units, etc. The 25-relation taxonomy of Bourque (2014) was tested against over 15,000 binominal lexemes from 106 languages and extended to a 29-relation scheme ("Bourque2") through the introduction of two new reversible relations. Bourque2 is then mapped onto Hatcher's (1960) four-relation scheme (extended by the addition of a fifth relation, similarity , as "Hatcher2"). This results in a two-tier system usable at different degrees of granularities. On account of its semantic proximity to compounding, metonymy is then taken into account, following Janda's (2011) suggestion that it plays a role in word formation; Peirsman and Geeraerts' (2006) inventory of 23 metonymic patterns is mapped onto Bourque2, confirming the identity of metonymic and binominal modification relations. Finally, Blank's (2003) and Koch's (2001) work on lexical semantics justifies the addition to the scheme of a third, superordinate level which comprises the three Aristotelean principles of similarity, contiguity and contrast.
-
Kottmann, N.; Studer, T.: Improving semantic query answering (2006)
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Hori, M.; Euzenat, J.; Patel-Schneider, P.F.: OWL Web Ontology Language XML Presentation Syntax (2003)
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