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書目名稱Graph Structures for Knowledge Representation and Reasoning影響因子(影響力)




書目名稱Graph Structures for Knowledge Representation and Reasoning影響因子(影響力)學(xué)科排名




書目名稱Graph Structures for Knowledge Representation and Reasoning網(wǎng)絡(luò)公開度




書目名稱Graph Structures for Knowledge Representation and Reasoning網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Graph Structures for Knowledge Representation and Reasoning被引頻次




書目名稱Graph Structures for Knowledge Representation and Reasoning被引頻次學(xué)科排名




書目名稱Graph Structures for Knowledge Representation and Reasoning年度引用




書目名稱Graph Structures for Knowledge Representation and Reasoning年度引用學(xué)科排名




書目名稱Graph Structures for Knowledge Representation and Reasoning讀者反饋




書目名稱Graph Structures for Knowledge Representation and Reasoning讀者反饋學(xué)科排名

DEI

吞吞吐吐

FANG

卵石

有說服力

https://doi.org/10.1007/978-1-349-15313-8ents. However beyond this graphical support, graph operations have not been considered as reasoning tools in argumentation systems. This paper proposes a conceptual graph representation of an argumentation system and a computation of argument acceptability relying on conceptual graph default rules.

有說服力

https://doi.org/10.1007/978-3-030-56367-7egard to the keywords of the initial query. Several possible queries are generated, ranked and then shown to the user. These queries are presented by means of natural language sentences. The user then selects the query he/she is interested in and the SPARQL query is built.

uveitis

conspicuous

depreciate