Computing FOAF Co-reference Relations with Rules and Machine Learning

Jennifer Sleeman and Tim FininUniversity of Maryland, Baltimore County

The Third International Workshop on Social Data on the Web, November 2010

http://ebiquity.umbc.edu/paper/html/id/506/

FOAF

Friend of a Friend (FOAF) vocabulary describes people and their relationships One of oldest and most widely used ontologies

Does not include a globally unique identifier Inverse functional properties (IFPs) help

Multiple foaf instances referring to the same person are common Increasingly so with more linked data

introduction foaf co-reference approach methodology evaluation conclusions

Linking dataData integration requires linking instances

from different data setsLinking foaf instances is a common and

typical use caseSindice reports 23 foaf instances all referring

to Sir Tim Berners LeeProbably more than my query revealedOnly a handful are linked via owl:sameAsAutomatically linking foaf instances is not

always easy

introduction foaf co-reference approach methodology evaluation conclusions

Example 1<swivt:Subject rdf:about="http://tw.rpi.edu/wiki/Special:URIResolver/Bijan_Parsia"><rdfs:label>Bijan Parsia</rdfs:label><swivt:page rdf:resource="http://tw.rpi.edu/wiki/Bijan_Parsia"/><rdfs:isDefinedBy rdf:resource="http://tw.rpi.edu/wiki/Special:ExportRDF/Bijan_Parsia"/><rdf:type rdf:resource="http://tw.rpi.edu/wiki/Special:URIResolver/Category-3APerson"/><property:Foaf-3Adepiction rdf:resource="http://tw.rpi.edu/wiki/Special:URIResolver/Anonymous.png"/><foaf:firstName rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Bijan</foaf:firstName><foaf:interest rdf:resource="http://tw.rpi.edu/wiki/Special:URIResolver/Category-3ASemantic_Web_Topic"/><foaf:name rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Bijan Parsia</foaf:name><foaf:surname rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Parsia</foaf:surname><property:Has_affiliation rdf:resource="http://tw.rpi.edu/wiki/Special:URIResolver/Manchester_University"/><property:Has_identifier rdf:resource="http://tw.rpi.edu/wiki/Special:URIResolver/Bijan_Parsia"/></swivt:Subject>

http://tw.rpi.edu/wiki/Special:ExportRDF/Bijan_Parsia

<foaf:Person rdf:ID="bparsia"> <foaf:mbox_sha1sum>f49a6854842c5fa76dc0edb8e82f8fe04fd56bc9</foaf:mbox_sha1sum> <foaf:firstName>Bijan</foaf:firstName> <foaf:surname>Parsia</foaf:surname> <foaf:name>Bijan Parsia</foaf:name> <foaf:homepage rdf:resource="http://trust.mindswap.org/cgi-bin/FilmTrust/foaf.cgi?user=bparsia"/> <foaf:img rdf:resource="http://www.mindswap.org/~bparsia/talks/uri-use/bijan.jpg"/> <foaf:depiction rdf:resource="http://www.mindswap.org/~bparsia/talks/uri-use/bijan.jpg"/> <foaf:nick>bparsia</foaf:nick> <foaf:holdsAccount> <foaf:OnlineAccount> <foaf:accountName>bparsia</foaf:accountName> <foaf:accountServiceHomepage rdf:resource="http://trust.mindswap.org/FilmTrust/"/> </foaf:OnlineAccount> </foaf:holdsAccount>

http://trust.mindswap.org/cgi-bin/FilmTrust/foaf.cgi?user=bparsia#tt0084827-bparpia

Common properties but can wesay this is the same person…

Example 2<foaf:Person>

<foaf:name>James A. Hendler</foaf:name>

<foaf:firstName>James</foaf:firstName>

<foaf:surname>Hendler</foaf:surname>

<foaf:publications>http://ebiquity.umbc.edu/papers/select/person/James/Hendler/</foaf:publications>

<foaf:homepage rdf:resource="http://www.cs.umd.edu/~hendler/"/>

<foaf:workInfoHomepage rdf:resource="http://www.cs.umd.edu/~hendler/"/>

http://ebiquity.umbc.edu/person/foaf/James/A./Hendler/foaf.rdf

<foaf:Person rdf:ID="jhendler"> <foaf:mbox_sha1sum>0b62d4242736e64be6138547c79a811b3e82fd52</foaf:mbox_sha1sum> <foaf:firstName>Jim</foaf:firstName> <foaf:surname>Hendler</foaf:surname> <foaf:name>Jim Hendler</foaf:name> <foaf:title>Tetherless World Constellation Chair</foaf:title> <foaf:homepage rdf:resource="http://trust.mindswap.org/cgi-bin/FilmTrust/foaf.cgi?user=jhendler"/> <foaf:homepage rdf:resource="http://www.cs.umd.edu/~hendler"/> <foaf:depiction rdf:resource="http://www.semanticgrid.org/q-iantbljim.jpg"/> <foaf:workplaceHomepage rdf:resource="http://owl.mindswap.org"/> <foaf:img rdf:resource="http://www.cs.umd.edu/~hendler/hendler.gif"/> <foaf:depiction rdf:resource="http://www.cs.umd.edu/~hendler/hendler.gif"/> <foaf:nick>jhendler</foaf:nick> <foaf:openID rdf:resource="http://jhendler.pip.verisignlabs.com/" /> <foaf:holdsAccount> <foaf:OnlineAccount> <foaf:accountName>jhendler</foaf:accountName> <foaf:accountServiceHomepage rdf:resource="http://trust.mindswap.org/FilmTrust/"/> </foaf:OnlineAccount> </foaf:holdsAccount>

http://www.cs.rpi.edu/~hendler/foaf.rdf

Aliases and slight namevariations…

Example 3<Agent rdf:about="http://identi.ca/user/53505"><mbox_sha1sum>08445a31a78661b5c746feff39a9db6e4e2cc5cf</mbox_sha1sum><name>David Wood</name><homepage rdf:resource="http://dw2-0.com"/><weblog rdf:resource="http://identi.ca/dw2"/><holdsAccount><OnlineAccount rdf:about="http://identi.ca/user/53505#acct"><accountServiceHomepage rdf:resource="http://identi.ca/"/><accountName>dw2</accountName><accountProfilePage rdf:resource="http://identi.ca/dw2"/><sioc:account_of rdf:resource="http://identi.ca/user/53505"/><sioc:follows rdf:resource="http://identi.ca/user/136#acct"/></OnlineAccount></holdsAccount>

http://identi.ca/dw2/foaf

<foaf:Person rdf:about="http://zepheira.com/team/dave/#me"> <foaf:name>David Wood</foaf:name> <foaf:title>Dr.</foaf:title> <foaf:givenname>David</foaf:givenname> <foaf:family_name>Wood</foaf:family_name> <foaf:nick>prototypo</foaf:nick> <foaf:mbox_sha1sum>37c8d030d4e615d05f31625b3460532a3f4e214e</foaf:mbox_sha1sum> <foaf:homepage rdf:resource="http://prototypo.blogspot.com/"/> <foaf:depiction rdf:resource="http://www.itee.uq.edu.au/~dwood/images/dave_w_0.jpg"/> <foaf:phone rdf:resource="tel:+1-(571)-331-3723"/> <foaf:workplaceHomepage rdf:resource="http://www.zepheira.com/"/> <foaf:workInfoHomepage rdf:resource="http://www.zepheira.com/team/dave"/> <foaf:schoolHomepage rdf:resource="http://www.vmi.edu/"/> <foaf:schoolHomepage rdf:resource="http://www.nps.navy.mil/"/> <foaf:schoolHomepage rdf:resource="http://www.itee.uq.edu.au/"/> <foaf:aimChatID>piprototypo</foaf:aimChatID>

http://www.itee.uq.edu.au/~dwood/dave.rdf#me

What if mbox_sha1sums aredifferent?

Example 3 cont.

<ms:Researcher rdf:ID="David_Wood" rdfs:label="David Wood"><foaf:name>David Wood</foaf:name><foaf:mbox><owl:Thing rdf:about="mailto:dwood@mindswap.org"/></foaf:mbox><foaf:homepage><foaf:Document rdf:about="http://www.mindswap.org/~dwood/"/></foaf:homepage><foaf:workInfoHomepage><foaf:Document rdf:about="http://www.mindswap.org/~dwood/"/></foaf:workInfoHomepage></ms:Researcher>

http://www.mindswap.org/2004/owl/mindswappers#David.Wood

Which David Wood was amindswapper?

Example 5<foaf:Person rdf:ID="jgolbeck"> <foaf:mbox_sha1sum>08445a31a78661b5c746feff39a9db6e4e2cc5cf</foaf:mbox_sha1sum> <foaf:firstName></foaf:firstName> <foaf:surname></foaf:surname> <foaf:name> </foaf:name> <foaf:homepage rdf:resource="http://trust.mindswap.org/cgi-bin/FilmTrust/foaf.cgi?user=jgolbeck"/> <foaf:img rdf:resource=""/> <foaf:depiction rdf:resource=""/> <foaf:nick>jgolbeck</foaf:nick> <foaf:holdsAccount> <foaf:OnlineAccount> <foaf:accountName>jgolbeck</foaf:accountName> <foaf:accountServiceHomepage rdf:resource="http://trust.mindswap.org/FilmTrust/"/> </foaf:OnlineAccount> </foaf:holdsAccount>

http://trust.mindswap.org/cgi-bin/FilmTrust/foaf.cgi?user=jgolbeck

<swivt:Subject rdf:about="http://tw.rpi.edu/wiki/Special:URIResolver/Jennifer_Golbeck">

<rdfs:label>Jennifer Golbeck</rdfs:label>

<swivt:page rdf:resource="http://tw.rpi.edu/wiki/Jennifer_Golbeck"/>

<rdfs:isDefinedBy rdf:resource="http://tw.rpi.edu/wiki/Special:ExportRDF/Jennifer_Golbeck"/>

<rdf:type rdf:resource="http://tw.rpi.edu/wiki/Special:URIResolver/Category-3AAssistant_Professor"/>

<rdf:type rdf:resource="http://tw.rpi.edu/wiki/Special:URIResolver/Category-3APerson"/>

<property:Foaf-3Adepiction rdf:resource="http://tw.rpi.edu/wiki/Special:URIResolver/Anonymous.png"/>

<foaf:firstName rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Jennifer</foaf:firstName>

<foaf:interest rdf:resource="http://tw.rpi.edu/wiki/Special:URIResolver/Category-3ASemantic_Web_Topic"/>

<foaf:name rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Jennifer Golbeck</foaf:name>

<foaf:surname rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Golbeck</foaf:surname>

http://tw.rpi.edu/wiki/Special:ExportRDF/Jennifer_Golbeck

Could jgolbeck and Jennifer Golbeck be the same person …

Example 5 cont.<rdf:RDF><foaf:Person><foaf:name>Jennifer Golbeck</foaf:name><foaf:mbox rdf:resource="mailto:golbeck@cs.umd.edu"/> <foaf:mbox rdf:resource="mailto:golbeck@mindswap.org"/><owl:sameAs rdf:resource="http://www.mindswap.org/2004/owl/mindswappers#Jennifer.Golbeck"/><foaf:workplaceHomepage rdf:resource="http://www.cs.umd.edu/~golbeck"/><foaf:currentProject rdf:resoruce="http://trust.mindswap.org"/><foaf:publications rdf:resource="http://www.mindswap.org/papers"/><foaf:knows rdf:resource="#danbri"/><rdfs:seeAlso rdf:resource="http://trust.mindswap.org/cgi-bin/getList.cgi"/>

http://www.cs.umd.edu/~golbeck/daml/golbeckFOAF.rdf

<ms:Researcher rdf:ID="Jennifer.Golbeck" rdfs:label="Jennifer Golbeck">

<rdfs:seeAlso rdf:resource="http://www.cs.umd.edu/~golbeck/daml/golbeckFOAF.rdf"/>

<foaf:name>Jennifer Golbeck</foaf:name>

<foaf:mbox><owl:Thing rdf:about="mailto:golbeck@cs.umd.edu"/></foaf:mbox>

<foaf:homepage><foaf:Document rdf:about="http://www.cs.umd.edu/~golbeck/"/></foaf:homepage>

<foaf:workInfoHomepage><foaf:Document rdf:about="http://www.mindswap.org/~golbeck/"/>

</foaf:workInfoHomepage>

</ms:Researcher>

http://www.mindswap.org/2004/owl/mindswappers#Jennifer.Golbeck

Which profile is most recent/relevant?

Our Contributions

Treating foaf smushing as entity co-referenceUse machine learning to train a classifier for

recognizing co-referent foaf instanceCombine this with rule-based evidenceUse of narrower RDF properties to express co-

reference, avoiding overuse of owl:sameAs Use of a greedy algorithm for iteratively clustering

co-referent entities and re-evaluating their potential co-reference relations

introduction foaf co-reference approach methodology evaluation conclusions

Co-Reference in FOAF

Approach problem like cross-document co-reference resolution in text

Match pairs FOAF agentsUse rules and propertiesAssign new properties to represent coref

and notCoref relationshipsCluster co-referent pairs

introduction foaf co-reference approach methodology evaluation conclusions

Cross-Document Co-reference Resolution

Determine when two documents mentionthe same entity

Are two documents that talk about “George Bush” talking about the same George Bush?Is a document mentioning “Mahmoud Abbas” referring to the same person as one mentioning “Muhammed Abbas”? What about “Abu Abbas”? “Abu Mazen”?

Drawing appropriate inferences frommultiple documents demands cross-document co-reference resolution

2008 NIST Text Analysis Conference

TAC KBP: Entity LinkingJohn Williams

Richard Kaufman goes a long way back with John Williams. Trained as a classical violinist, Californian Kaufman started doing session work in the Hollywood studios in the 1970s. One of his movies was Jaws, with Williams conducting his score in recording sessions in 1975...

John Williams author 1922-1994

J. Lloyd Williams botanist 1854-1945

John Williams politician 1955-

John J. Williams US Senator 1904-1988

John Williams Archbishop 1582-1650

John Williams composer 1932-

Jonathan Williams poet 1929-

Michael Phelps

Debbie Phelps, the mother of swimming star Michael Phelps, who won a record eight gold medals in Beijing, is the author of a new memoir, ...

Michael Phelps swimmer 1985-

Michael Phelps biophysicist 1939-

Michael Phelps is the scientist most often identified as the inventor of PET, a technique that permits the imaging of biological processes in the organ systems of living individuals. Phelps has ...

Given an entity mention in an article, find the link to the right Wikipedia entity if one exists.

2009 NIST TAC Knowledge Base Population Track

Smushing

Smushing is the traditional term used for recognizing that two “blank nodes” refer to the same thing and merging them

Past work on smushing has exploited IFPs (e.g., foaf:mbox), heuristic similarity metrics and custom SPARQL queries

owl:sameAs is often used to relate smushed nodes, enabling a reasoner to effect the merging

rdf:seeAlso used to find related foaf data

introduction foaf co-reference approach methodology evaluation conclusions

Smushing

introduction foaf co-reference approach methodology evaluation conclusions

foaf:Person

"foo@gmail.com"

rdfs:type

foaf:mbox

foaf:knowsfoaf:nick”bar"

owl:sameAs

foaf:mbox

Smushing

introduction foaf co-reference approach methodology evaluation conclusions

foaf:Person

"foo@gmail.com"

rdfs:type

foaf:knowsfoaf:nick”bar"

foaf:mbox

owl:sameAs considered harmful

Known problems– Temporally qualified data (Ding vs. Ding)– Noisy data (Clinton vs. Clinton)– Referentially opaque contexts (John likes the

Morning Star beautiful)Halpin et. Al (2010) suggest a vocabulary for

similarity relations similarity.owlWe use two weaker predicates: coref & notCoref– Defer the sameAs problem to applications

introduction foaf co-reference approach methodology evaluation conclusions

Co-Reference in FOAF

coref: transitive, symmetric and reflexive; has sameAs as subproperty

notCoref: symmetric and irreflexive but not transitive; has differentFrom as subproperty

:coref a owl:TransitiveProperty, owl:SymmetricProperty, owl:ReflexivePropertyowl:sameAs rdfs:subPropertyOf :coref.:notCoref a owl:SymmetricProperty, owl:IrreflexiveProperty.owl:differentFrom rdfs:subPropertyOf :notCoref.{?a :notCoref ?b. ?b :coref ?c.} => {?a :notCoref ?c}{?a foaf:knows ?b.} => {?a :notCoref ?b}

The :coref and :notCoref properties that we use instead of owl:sameAs

introduction foaf co-reference approach methodology evaluation conclusions

Batch Approach

Given a potentially large set of foaf instancesGenerate candidate pairsEvaluate each pair for co-reference

Using rules and classifier independentlyEach results in a {coref, notCoref, unknown}

decisionTrust rules over classifier

Designate pairs as co-referentCreate Clusters

introduction foaf co-reference approach methodology evaluation conclusions

Ingest

Extract triples from FOAF profilesAdd each foaf agent as new entity in

databaseEntity URLs followed in foaf:knows graph to

get additional information

introduction foaf co-reference approach methodology evaluation conclusions

Approach: System Architecture

introduction foaf co-reference approach methodology evaluation conclusions

ingestioningestion

candidate pair

generation

candidate pair

generation

rule-based reasoning

rule-based reasoning

machine learning

machine learning

Model Generation

Abstract entitygeneration

Potential pairs: reduces classifier workload

deductive decisions

deductive decisions predictionspredictions

clusters formnew abstract entities

Co-referent designation and clusteringCo-referent designation and clustering

Candidate Pairs

Filter pairs reduce matching setUse simple string matching predicates

Dice score for 3-gramsApply both to values of common properties

and also cross-property valuesExperiment 2 ~30% reduction Reductions vary based on data set

introduction foaf co-reference approach methodology evaluation conclusions

Input data sources

FOAF profiles extracted from SwoogleAlso used URLS extracted from tests

conducted in previous work

Distribution of URLs from Experiment 2

introduction foaf co-reference approach methodology evaluation conclusions

Methodology: Rule-based ModelRules conclude that two instances are co-

referent, not co-referent or draw no conclusion (the most common outcome)

Basic co-reference rule:{?p a owl:IFP. ?a ?p ?x. ?b ?p ?x) => {?a :coref ?b}

{?p a owl:FP . ?a ?p ?x. ?a ?p ?y.) => { ?x :coref ?y}

introduction foaf co-reference approach methodology evaluation conclusions

Methodology: Rule-based Model In text processing, very similar name mentions

in a document more likely to be co-referent It also is used in disambiguating name men-

tions in citations in a single paper or Web pageA similar heuristic is useful for a “knows graph”

extracted from a single foaf profile

{?a foaf:knows ?b. ?a foaf:knows ?c. ?b neq ?c} => {?b :notCoref ?c}

introduction foaf co-reference approach methodology evaluation conclusions

Methodology – Vector ModelSupport Vector Machine linear kernelFeatures:– Match/nomatch of any IFPs– Distance measures over common property

values (Levenshtein & 3-gram Dice score)– Alias and entity mention resolution– Property specific feature comparison– Knows graph comparisons: Jaccard coef of

similarity of foaf names of one-hop neighbors

introduction foaf co-reference approach methodology evaluation conclusions

Methodology: Clustering

Pairs form clustersClusters used as part of system evaluationCan result in:– Entity to Entity pairing

– Cluster to Entity pairing

– Cluster to Cluster pairing

Greedy process with a confidence thresholdUse rule-based model to eliminate known

non-coreferent pairs

introduction foaf co-reference approach methodology evaluation conclusions

Methodology – Clustering

Instance matching can result in new cluster formation and cluster matching can result in merged clusters.

introduction foaf co-reference approach methodology evaluation conclusions

Evaluation

Two experiments– E1: 50,000 triples, over 500 entity

mentions, 600 classes used for training– E2: 250,000 triples, over 3500 entity

mentions, over 1800 classes for training 10-fold cross-validation tests

introduction foaf co-reference approach methodology evaluation conclusions

Evaluation

Pairs Rule Conclusion

9138326 differentFrom Undetermined

47184 inverse functional Undetermined

2402 inverse functional Co-referent

8687410 knows graph Undetermined

9138326 sameAs Undetermined

1047874 knows Not Co-referent

For E1: 900 pairs non-match, majority undetermined

E2: Results shown below

introduction foaf co-reference approach methodology evaluation conclusions

Evaluation

Results promisingDuring our E2 clustering phase, the first

phase 90% accuracySecond phase no new relationships among

pairs, cluster to cluster pairing occurred

Classification Results using 10-fold Validation

introduction foaf co-reference approach methodology evaluation conclusions

Evaluation

Retrieving additional FOAF profiles based on knows graph

Quickly retrieve large number of entitiesTightly linked– reduced diversity of analyzed data–more entities that are co-referent

Future experiments: a diversity filter spanning domains

introduction foaf co-reference approach methodology evaluation conclusions

Future WorkEvaluating the contribution of each rule and

SVM feature to performanceOther ML approaches, e.g., markov logic, EMExploiting better clustering algorithmsAdding more features, e.g. non-foaf vocabu-

lary, non-RDF data (e.g., hosting site)Applying approach to other RDF instancesScalability:

Providing a non-batch, streaming serviceOffering a coref Web service

introduction foaf co-reference approach methodology evaluation conclusions

Conclusions

We can treat instance linking as co-reference resolution & exploit in-doc and xdoc distinction

Good results with an ensemble approach combining rules and an SVM classifier

Apply clustering to form groups of co-referent relations and reprocess

Promising initial results

introduction foaf co-reference approach methodology evaluation conclusions

http://ebiquity.umbc.edu/http://ebiquity.umbc.edu/