Smart city resource recommendation method and system based on knowledge graph
The invention provides a smart city data resource recommendation method and system based on a knowledge graph. The system comprises a candidate resource recall module, a knowledge graph embedding module, a knowledge graph extraction module and a recommendation module based on a deep network model. A...
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creator | LI CHAO YANG PEIQIN GUAN ZHELIN SHI HUICHANG |
description | The invention provides a smart city data resource recommendation method and system based on a knowledge graph. The system comprises a candidate resource recall module, a knowledge graph embedding module, a knowledge graph extraction module and a recommendation module based on a deep network model. According to the recommendation system, a user portrait is enhanced by associating triples, the relation between a user and resources is mined by utilizing a meta-graph instance, and an attention mechanism is introduced on the basis of an MLP model to consider the contribution degree of different meta-graphs to a result, so that the recommendation result is more accurate and more interpretable.
本发明提出了一种基于知识图谱的智慧城市数据资源推荐方法和系统,所述系统包括候选资源召回模块、知识图谱嵌入模块、知识图谱提取模块和基于深度网络模型的推荐模块。本发明的推荐系统通过关联三元组增强用户画像,利用元图实例来挖掘用户和资源之间的联系,并在MLP模型基础上引入注意力机制以考虑不同元图对结果的贡献度,从而使推荐结果更精确更具可解释性。 |
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本发明提出了一种基于知识图谱的智慧城市数据资源推荐方法和系统,所述系统包括候选资源召回模块、知识图谱嵌入模块、知识图谱提取模块和基于深度网络模型的推荐模块。本发明的推荐系统通过关联三元组增强用户画像,利用元图实例来挖掘用户和资源之间的联系,并在MLP模型基础上引入注意力机制以考虑不同元图对结果的贡献度,从而使推荐结果更精确更具可解释性。</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; HANDLING RECORD CARRIERS ; PHYSICS ; PRESENTATION OF DATA ; RECOGNITION OF DATA ; RECORD CARRIERS</subject><creationdate>2021</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210903&DB=EPODOC&CC=CN&NR=113343100A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76290</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210903&DB=EPODOC&CC=CN&NR=113343100A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>LI CHAO</creatorcontrib><creatorcontrib>YANG PEIQIN</creatorcontrib><creatorcontrib>GUAN ZHELIN</creatorcontrib><creatorcontrib>SHI HUICHANG</creatorcontrib><title>Smart city resource recommendation method and system based on knowledge graph</title><description>The invention provides a smart city data resource recommendation method and system based on a knowledge graph. The system comprises a candidate resource recall module, a knowledge graph embedding module, a knowledge graph extraction module and a recommendation module based on a deep network model. According to the recommendation system, a user portrait is enhanced by associating triples, the relation between a user and resources is mined by utilizing a meta-graph instance, and an attention mechanism is introduced on the basis of an MLP model to consider the contribution degree of different meta-graphs to a result, so that the recommendation result is more accurate and more interpretable.
本发明提出了一种基于知识图谱的智慧城市数据资源推荐方法和系统,所述系统包括候选资源召回模块、知识图谱嵌入模块、知识图谱提取模块和基于深度网络模型的推荐模块。本发明的推荐系统通过关联三元组增强用户画像,利用元图实例来挖掘用户和资源之间的联系,并在MLP模型基础上引入注意力机制以考虑不同元图对结果的贡献度,从而使推荐结果更精确更具可解释性。</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>HANDLING RECORD CARRIERS</subject><subject>PHYSICS</subject><subject>PRESENTATION OF DATA</subject><subject>RECOGNITION OF DATA</subject><subject>RECORD CARRIERS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2021</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNij0KwkAQRtNYiHqH8QBClvUCEhQbbbQP4-5nEsz-sDMiub0pPIDVe_DesrrcAhclN-hEBZLexWEWl0JA9KxDihSgffLE0ZNMogj0YIGnOb1i-ozwHagrnPt1tXjyKNj8uKq2p-O9Oe-QUwvJ7BChbXM1xtq9NXV9sP88XwSDNlg</recordid><startdate>20210903</startdate><enddate>20210903</enddate><creator>LI CHAO</creator><creator>YANG PEIQIN</creator><creator>GUAN ZHELIN</creator><creator>SHI HUICHANG</creator><scope>EVB</scope></search><sort><creationdate>20210903</creationdate><title>Smart city resource recommendation method and system based on knowledge graph</title><author>LI CHAO ; YANG PEIQIN ; GUAN ZHELIN ; SHI HUICHANG</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN113343100A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2021</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>HANDLING RECORD CARRIERS</topic><topic>PHYSICS</topic><topic>PRESENTATION OF DATA</topic><topic>RECOGNITION OF DATA</topic><topic>RECORD CARRIERS</topic><toplevel>online_resources</toplevel><creatorcontrib>LI CHAO</creatorcontrib><creatorcontrib>YANG PEIQIN</creatorcontrib><creatorcontrib>GUAN ZHELIN</creatorcontrib><creatorcontrib>SHI HUICHANG</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>LI CHAO</au><au>YANG PEIQIN</au><au>GUAN ZHELIN</au><au>SHI HUICHANG</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Smart city resource recommendation method and system based on knowledge graph</title><date>2021-09-03</date><risdate>2021</risdate><abstract>The invention provides a smart city data resource recommendation method and system based on a knowledge graph. The system comprises a candidate resource recall module, a knowledge graph embedding module, a knowledge graph extraction module and a recommendation module based on a deep network model. According to the recommendation system, a user portrait is enhanced by associating triples, the relation between a user and resources is mined by utilizing a meta-graph instance, and an attention mechanism is introduced on the basis of an MLP model to consider the contribution degree of different meta-graphs to a result, so that the recommendation result is more accurate and more interpretable.
本发明提出了一种基于知识图谱的智慧城市数据资源推荐方法和系统,所述系统包括候选资源召回模块、知识图谱嵌入模块、知识图谱提取模块和基于深度网络模型的推荐模块。本发明的推荐系统通过关联三元组增强用户画像,利用元图实例来挖掘用户和资源之间的联系,并在MLP模型基础上引入注意力机制以考虑不同元图对结果的贡献度,从而使推荐结果更精确更具可解释性。</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING HANDLING RECORD CARRIERS PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS |
title | Smart city resource recommendation method and system based on knowledge graph |
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