My M.Sc. thesis in Isfahan University of Technology, Fall 2012

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Apriori
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TID Items
100 1 3 4
200 2 3 5
300 1 2 3 5
400 2 5
Database D itemset sup.
{1} 2
{2} 3
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{4} 1
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itemset sup.
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Scan D
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itemset
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itemset sup
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itemset sup
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C3 L3itemset
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Scan D itemset sup
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pd:cygri
Richard Cyganiak
dbpedia:Berlin
foaf:name
foaf:based_near
foaf:Person
rdf:type
pd:cygri = http://richard.cyganiak.de/foaf.rdf#cygri
dbpedia:Berlin = http://dbpedia.org/resource/Berlin

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Victoria NebotRafael Berlanga
•Finding association rules in semantic web data
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Victoria NebotRafael Berlanga
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Victoria NebotRafael Berlanga
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CREATE MINING MODEL <Dataset Path>
{
?patient RESOURCE TARGET
?drug RESOURCE
?jadi LITERAL
?disease RESOURCE PREDICT
?report RESOURCE CONTEXT
}
WHERE
{
?patient rdf:type Patient.
?drug rdf:type Drug.
?disease rdf:type Disease.
?report rdf:type Report.
?report damageIndex ?jadi.
}

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Victoria NebotRafael Berlanga
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TID Subject Aggregation Path Object Feature
1 PTN_XY21 (VISIT1,RHEX1) Malformation Disease
1 PTN_XY21 (VISIT1,RHEX1) RHEX1
2 PTN_XY21 (VISIT1,TREAT1) Methotrexate Drug
3 PTN_XY21 (VISIT2,RHEX2) Malformation Disease
3 PTN_XY21 (VISIT2,RHEX2) RHEX2
3 PTN_XY21 (VISIT2,RHEX2) Bad rotation Disease
4 PTN_XY21 (VISIT2,TREAT2) Methotrexate Drug
4 PTN_XY21 (VISIT2,TREAT2) Corticosteroids Drug
TID Object
1 {Malformation, RHEX1}
2 {Methotrexate}
3 {Malformation, RHEX2, Bad rotation}
4 {Methotrexate, Corticosteroids}
Subject Aggregation Path Object Feature
PTN_XY21 (VISIT1,RHEX1,ULTRA1) Malformation Disease
PTN_XY21 (VISIT1,RHEX1) RHEX1
PTN_XY21 (VISIT1,TREAT1,DT1) Methotrexate Drug
PTN_XY21 (VISIT2,RHEX2,ULTRA2) Malformation Disease
PTN_XY21 (VISIT2,RHEX2) RHEX2
PTN_XY21 (VISIT2,RHEX2,ULTRA3) Bad rotation Disease
PTN_XY21 (VISIT2,TREAT2,DT2) Methotrexate Drug
PTN_XY21 (VISIT2,TREAT2,DT3) Corticosteroids Drug
… … … …

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Ziawasch AbedjanFelix Naumann
•Context and Target Configurations for Mining RDF Data
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Venkata Narasimha et al
•LiDDM: A Data Mining System for Linked Data
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List of ItemsTid
A,B,ET001
B,DT002
B,CT003
A,B,DT004
A,CT005
B,CT006
A,BT007
A,B,C,ET008
A,B,CT009

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List of ItemsTid
a,d,eT001
b,a,f,g,hT002
b,a,d,fT003
b,a,cT004
a,d,g,kT005
b,d,g,c,iT006
b,d,g,r,jT007

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(SPARQL)
(Linked Data)
MinConf, MinSup

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Entity ID
Relation ID
Relation ID
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InputEntities
Relations
Source Entities List
Source Entities List
Is Large
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Relation IDNode ID
Item
Item 1 Item 2 Item n…
Itemset
ConfidenceItemItem 1 Item 2 Item n…
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Support
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NodeInfo

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3-Itemset
Association Rules

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1. Algorithm 1. Mining association rules from semantic web data
2. SWApriori(DS, MinSup, MinConf)
3. Input:
4. DS: Dataset that consists triples (Subject, Predicate, and Object)
5. MinSup: Minimum support
6. MinConf: Minimum confidence
7. Output:
8. AllFIs: Large itemsets
9. Rules: Association rules
10. Variables:
11. FIs, Candidates: List of Itemsets
12. IS, IS1, IS2, IS3: Itemset (multiple items)
13. NodeInfoList: List of NodeInfo
14. Begin
15. Traverse triples and discretize objects
16. Delete triples which their subject, predicate or object has frequency less than MinSup
17. Convert input dataset's data to numerical values
18. Store converted data into NodeInfo instances
19. NodeInfoList = NodeInfo instances

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Generate2LargeItemset
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GenerateRules
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S, P, O
S, P, O
S, P, O
S, P, O
S, P, O
S, P, O
S, P, O
S, P, O
S, P, O
S, P, O
S, P, O
S, P, O
S, P, O
S, P, O
S, P, O
S, P, O
S, P, O
S, P, O
DS1 DS2
DS3
DS1/Iran owl:Population xsd:int 75,000,000
DS1/Iran ont:Border DS1/Afghanistan
DS1/Iran ont:West DS2/Iraq
DS1/Iran owl:sameAs DS2/Iran
DS1/Iran owl:sameAs DS3/Xr.36O77z
ont:West

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SELECT * {
?Subject rdf:type <http://dbpedia.org/ontology/Country> .
?Subject ?Predicate ?Object
}
ORDER BY ?Subject
http://dbpedia.org/resource/[CountryName]
SELECT ?Subject ?Predicate ?Object
WHERE
{
?Subject ?Predicate ?Object
}
ORDER BY ?Subject
http://rdf.freebase.com/ns/m.03shp

http://rdf.freebase.com/rdf/en/[CountryName]

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2-Large Itemset
NaN

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2-Large Itemset
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FreebaseFactBookDBPedia
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 R.Ramezani, M.H.Saraee, M.A.Nematbakhsh. “A New approach to mining
Association Rules from Semantic Web data”. Submitted to International Journal
of Semantic Web and Information Systems (IJSWIS)

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