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Titlebook: Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence; Second China Confere Juanzi Li,Ming Zhou,Jianfeng Du Confere

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发表于 2025-3-21 18:37:48 | 显示全部楼层 |阅读模式
书目名称Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence
副标题Second China Confere
编辑Juanzi Li,Ming Zhou,Jianfeng Du
视频video
丛书名称Communications in Computer and Information Science
图书封面Titlebook: Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence; Second China Confere Juanzi Li,Ming Zhou,Jianfeng Du Confere
描述.This book constitutes the refereed proceedings of the Second China Conference on Knowledge Graph and Semantic Computing, CCKS 2017, held in Chengdu, China, in August 2017.. .The 11 revised full papers and 6 revised short papers presented were carefully reviewed and selected from 85 submissions. The papers cover wide research fields including the knowledge graph, the Semantic Web, linked data, NLP, knowledge representation, graph databases..
出版日期Conference proceedings 2017
关键词knowledge graph; semantic computing; semantics; semantic web; knowledge base; learning systems; knowledge
版次1
doihttps://doi.org/10.1007/978-981-10-7359-5
isbn_softcover978-981-10-7358-8
isbn_ebook978-981-10-7359-5Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer Nature Singapore Pte Ltd. 2017
The information of publication is updating

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发表于 2025-3-21 23:46:13 | 显示全部楼层
Tensor-Based Representation and Reasoning of Horn-, Ontologies,ation, which is an important logical reasoning service for ontology-based applications. We show that the soundness and completeness of ontology materialization can be guaranteed by using tensor operations.
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CrowdGeoKG: Crowdsourced Geo-Knowledge Graph,them with human geography knowledge from Wikidata. We further exploited the part of CrowdGeoKG in China, studying the linkage between OpenStreetMap geo-entities and Wikidata geo-entities. CrowdGeoKG is stored in both RDF (Resource Description Framework) and JSON-LD formats, and shared for re-usage on an open knowledge graph community named OpenKG.
发表于 2025-3-22 08:58:04 | 显示全部楼层
1865-0929 Chengdu, China, in August 2017.. .The 11 revised full papers and 6 revised short papers presented were carefully reviewed and selected from 85 submissions. The papers cover wide research fields including the knowledge graph, the Semantic Web, linked data, NLP, knowledge representation, graph databa
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A Hybrid Method to Sentiment Analysis for Chinese Microblog,e microblog. This hybrid approach combines the basic techniques of natural language processing (NLP) and machine learning to determine the semantic orientation for Chinese microblog. The hybrid method is tested on two public data sets and the results show that our method is effective.
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Path-Based Learning for Plant Domain Knowledge Graph,th by combining attributes and hyponymy relations, and embeds them to a lower dimensional space as well. We conduct extensive experiments on link prediction task where the performance is measured by mean rank and Hit@10. The results show that our new model significantly outperforms other competing methods on several different tasks.
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