Category Archives: KnowledgeGraph

1、下载apache-jena-fuseki和apache-jena
https://jena.apache.org/download/index.cgi

2、将上一篇教程的nt文件转换为tdb格式

cd apache-jena-3.9.0\bat
tdbloader.bat --loc="PATH_TO_TDB\tdb" "PATH_TO_NT\movies_mapping.nt"

3、切换到apache-jena-fuseki-3.9.0目录，启动一次服务，然后退出

4、将教程1里面的Movies.owl，拷贝到apache-jena-fuseki-3.9.0\run\databases路径下面，并重命名为Movies.ttl

5、创建配置文件apache-jena-fuseki-3.9.0\run\configuration\fuseki_conf.ttl

@prefix fuseki: <http://jena.apache.org/fuseki#> . 
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . 
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . 
@prefix tdb: <http://jena.hpl.hp.com/2008/tdb#> . 
@prefix ja: <http://jena.hpl.hp.com/2005/11/Assembler#> . 
@prefix : <http://base/#> . 

<#service> rdf:type fuseki:Service ; 
    fuseki:name "movies" ;
    fuseki:serviceQuery "sparql" ;
    fuseki:dataset <#dataset> ; 
    fuseki:serviceReadGraphStore      "get" ;
    fuseki:serviceReadWriteGraphStore "data" ;
    fuseki:serviceUpdate              "update" ;
    fuseki:serviceUpload              "upload"
    . 

<#dataset> rdf:type ja:RDFDataset ;
	ja:defaultGraph <#modelInf> ;
	.

<#modelInf> 
    rdf:type ja:InfModel ;
    #ja:reasoner [ja:reasonerURL <http://jena.hpl.hp.com/2003/OWLFBRuleReasoner>]  
    ja:reasoner [ 
        ja:reasonerURL <http://jena.hpl.hp.com/2003/GenericRuleReasoner> ; 
        ja:rulesFrom <file:///D:/ProjectsMy/KG/apache-jena-fuseki-3.9.0/run/databases/Rules.ttl> ] ; 
    ja:baseModel <#baseModel> ; 
    . 

<#baseModel> rdf:type tdb:GraphTDB ; 
    tdb:location "D:/ProjectsMy/KG/workspace/data/tdb" ; 
    tdb:unionDefaultGraph true ; 
    .

6、创建规则文件apache-jena-fuseki-3.9.0\run\databases\Movies.ttl
这个规则规定了，演过喜剧的演员，叫做喜剧演员（Comedian）

@prefix xsd: <XML Schema> .
@prefix owl: <http://www.w3.org/2002/07/owl#> .
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix : <https://www.neohope.com/hansen/ontologies/2018/movies#> .

[ruleComedian: (?aPerson :hasActedIn ?aMovie) (?aMovie :hasGenre ?aGenre) (?aGenre :genreName '喜剧') -> (?aPerson rdf:type :Comedian)]
[ruleInverse: (?aPerson :hasActedIn ?aMove) -> (?aMovie :hasActor ?aPerson)]

7、启动apache-jena-fuseki-3.9.0

8、访问http://localhost:3030/

9、进行查询，上一篇的例子也都可以用
http://localhost:3030/dataset.html?tab=query&ds=/movies

PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
prefix owl: <http://www.w3.org/2002/07/owl#>
prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>
prefix : <https://www.neohope.com/hansen/ontologies/2018/movies#>

SELECT ?name WHERE {
?aComedian rdf:type :Comedian.
?aComedian :personName ?name.
}
LIMIT 10

10、通过python访问
https://github.com/neohope/kg-demo-for-movie/tree/master/src/query-jena.py

参考链接：
https://zhuanlan.zhihu.com/knowledgegraph
https://github.com/SimmerChan/KG-demo-for-movie

PS：
参考教程中，原作者通过结巴分词+正则匹配+Jena，实现了一个简单的问答系统，感兴趣的话，大家可以看下。

1、安装MySQL5，并新建movies库

2、导入数据
https://github.com/neohope/kg-demo-for-movie/tree/master/data/movies.sql

3、下载d2rq，并配置好JDK环境变量
http://d2rq.org/

4、利用d2rq生成mapping

generate-mapping -u movie -p password -o movies_mapping.ttl jdbc:mysql:///movies

5、手工编辑ttl，任务如下
设置正确的域名
修正类名与属性名
删除一些不需要的字段
修改前后的数据可以在这里找到
https://github.com/neohope/kg-demo-for-movie/tree/master/data/movies_mapping.ttl
https://github.com/neohope/kg-demo-for-movie/tree/master/data/movies_mapping_ok.ttl

6、输出RDF文件，用于后续的教程

dump-rdf.bat -o movies_mapping.nt movies_mapping_ok.ttl

7、启动d2r服务

d2r-server.bat movies_mapping_ok.ttl

8、访问及浏览数据
http://localhost:2020/

9、查询
http://localhost:2020/snorql/

#周星驰演过的电影
SELECT ?title WHERE {
  ?aPerson rdf:type :Person.
  ?aPerson :personName '周星驰'.
  ?aPerson :hasActedIn ?aMovie.
  ?aMovie :movieTitle ?title
}
LIMIT 10


#英雄的演员
SELECT ?actor WHERE {
  ?aMovie rdf:type :Movie.
  ?aMovie :movieTitle '英雄'.
  ?aPerson :hasActedIn ?aMovie.
  ?aPerson :personName ?actor
}
LIMIT 10


#巩俐参演的，评分高于7的电影
SELECT ?title WHERE {
  ?aPerson rdf:type :Person.
  ?aPerson  :personName '巩俐'.
  ?aPerson  :hasActedIn ?aMovie.
  ?aMovie :movieTitle ?title.
  ?aMovie :movieRating ?rating.
  FILTER (?rating>=7)
}
LIMIT 10

10、通过python访问
https://github.com/neohope/kg-demo-for-movie/tree/master/src/query-d2rq.py

参考链接：
https://zhuanlan.zhihu.com/knowledgegraph
https://github.com/SimmerChan/KG-demo-for-movie

1、下载Protege工具

https://protege.stanford.edu/

2、安装JDK，并在配置好JDK环境变量

3、打开Protege

4、在Active Ontology页面，填写两个IRI，我分别填写了下面的数值

#Ontology IRI
https://www.neohope.com/hansen/ontologies/2018/movies
#Ontology Version IRI
https://www.neohope.com/hansen/ontologies/2018/movies/1.0.0

5、在Entities页面，切换到Classes，新建三个Class

Genre
Movie
Person

6、Entities页面，切换到Data properties，新建以下属性

genereId{Domain=Genre,Ranges=xsd:string}
genereName{Domain=Genre,Ranges=xsd:string}
movieId{Domain=Movie,Ranges=xsd:string}
movieIntroduction{Domain=Movie,Ranges=xsd:string}
movieRating{Domain=Movie,Ranges=xsd:string}
movieReleaseDate{Domain=Movie,Ranges=xsd:string}
movieTitile{Domain=Movie,Ranges=xsd:string}
personAppellation{Domain=Person,Ranges=xsd:string}
->personEnglishName{Domain=Person,Ranges=xsd:string}
->personName{Domain=Person,Ranges=xsd:string}
personBiography{Domain=Person,Ranges=xsd:string}
personbirthDay{Domain=Person,Ranges=xsd:string}
personBirthPlace{Domain=Person,Ranges=xsd:string}
personDeathDay{Domain=Person,Ranges=xsd:string}
personId{Domain=Person,Ranges=xsd:string}

7、Entities页面，切换到Object Properties，新建以下属性

hasActedIn{Domain=Person,Range=Movie,InverseOf=hasActor}
hasActor{Domain=Movie,Range=Person}
hasGenre{Domain=Person,Range=Genre}

8、保存为Movies.owl，这个文件可以在后面jena的例子中用到

9、建模后的结果，可以在这里获取：
https://github.com/neohope/kg-demo-for-movie/tree/master/protege

参考链接：
https://zhuanlan.zhihu.com/knowledgegraph
https://github.com/SimmerChan/KG-demo-for-movie