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

獨(dú)裁者

書目名稱Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence影響因子(影響力)




書目名稱Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence影響因子(影響力)學(xué)科排名




書目名稱Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence網(wǎng)絡(luò)公開度




書目名稱Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence被引頻次




書目名稱Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence被引頻次學(xué)科排名




書目名稱Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence年度引用




書目名稱Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence年度引用學(xué)科排名




書目名稱Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence讀者反饋




書目名稱Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence讀者反饋學(xué)科排名

培養(yǎng)

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.

heckle

HACK

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.

蓋他為秘密

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

ADOPT

反省

偽證

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.

故意

引起

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.