Giter Club home page Giter Club logo

resim's Introduction

DESCRIPTION

The RESIM.jar file is an implementation of RESIM (REsource SIMilarity) measure. This measure is designed to calculate the semantic similarity between two resources in a Knowlege Graph (e.g., DBpedia, Wikidata, zhishi.me) with a SPARQL Endpoint. RESIM is presented in [1] at first, and then it has been improved in [2]. The summary of the measure is presented in [3]. The implementation extends the measure further by enabling different properties for two resources, e.g., for incoming indirect link between dbpedia:Steve_Jobs and dbpedia:Apple_Inc., it can be connected by dbpedia:Steve_Jobs<-dbpedia-owl:keyPerson<-dbpedia:NexT->dbpedia-owl:successor->dbpedia:Apple_Inc. while in the paper we restrict the property should be the same.

When writing a paper or producing a software application, tool, or interface based on the library, please kindly cite the source [2].

REQUIREMENT

  • Java 1.7
  • JENA 2.11.2

Simply add jena files as well as RESIM.jar file in your building path to start.

alt tag

EXAMPLE 1

The example shows using RESIM to calculate the similarity between HongKong and Singapore Wikidata entities. inbound and outbound properties are given based on your selected domain (e.g., Music). This example use predefined "prefixList" for SPARQL.

public static void main(String[] args) {

	// Wikidata settings - must use prefix format
	ResourceSimilarityMeasure rsmForWikidata = new ResourceSimilarityMeasure( 
						PropertyRestriction.SamePropertyPath,
						"https://query.wikidata.org/sparql", 
						prefixList, null, 
						includeInboundPropertyList_wikidata, 
						includeOutboundPropertyList_wikidata, 
						null, null);
	
	// print similarity between HongKong and Singapore
	System.out.println(rsmForWikidata.getSimilarity("wd:Q8646", "wd:Q334", 2));
}

// prefix list
final static String prefixList = "PREFIX wdt: <http://www.wikidata.org/prop/direct/>\n" 
        				+ "PREFIX wd: <http://www.wikidata.org/entity/>\n";

// outbound properties used for consideration
final static List<String> includeOutboundPropertyList_wikidata = Arrays.asList(
		"wdt:P31",
		"wdt:P17",
		"wdt:P131",
		"wdt:P190",
		"wdt:P910",
		"wdt:P47",
		"wdt:P1376",
		"wdt:P1464",
		"wdt:P1792",
		"wdt:P1465",
		"wdt:P150",
		"wdt:P421",
		"wdt:P1343",
		"wdt:P361",
		"wdt:P163",
		"wdt:P6"
		);

// inbound properties used for consideration
final static List<String> includeInboundPropertyList_wikidata = Arrays.asList(
		"wdt:P19",
		"wdt:P20",
		"wdt:P131",
		"wdt:P937",
		"wdt:P159",
		"wdt:P276",
		"wdt:P190",
		"wdt:P740",
		"wdt:P840",
		"wdt:P971",
		"wdt:P301",
		"wdt:P915",
		"wdt:P551",
		"wdt:P36",
		"wdt:P47",
		"wdt:P1408",
		"wdt:P931",
		"wdt:P291",
		"wdt:P150",
		"wdt:P17",
		"wdt:P706",
		"wdt:P138",
		"wdt:P1071",
		"wdt:P921",
		"wdt:P27",
		"wdt:P1001",
		"wdt:P127",
		"wdt:P180",
		"wdt:P504",
		"wdt:P1427",
		"wdt:P119",
		"wdt:P1444",
		"wdt:P495"
		);

EXAMPLE 2

The example shows using RESIM to calculate the similarity between HongKong and Singapore DBpedia entities. inbound and outbound properties are given based on your selected domain (e.g., Music). This example shows without prefix list for SPARQL.

public static void main(String[] args) {
	
	// DBpedia settings - without prefix list format
	ResourceSimilarityMeasure rsmForDBpedia = new ResourceSimilarityMeasure(
						PropertyRestriction.SamePropertyPath,
						"http://dbpedia.org/sparql", 
						null, null, 
						includeInboundPropertyList_dbpedia, 
						includeOutboundPropertyList_dbpedia, 
						null, null);	
	
	System.out.println(
	rsmForDBpedia.getSimilarity("<http://dbpedia.org/resource/Hong_Kong>", "<http://dbpedia.org/resource/Singapore>", 2));

}

// DBpeida outbound properties
final static List<String> includeOutboundPropertyList_dbpedia = Arrays.asList(
		"<http://purl.org/dc/terms/subject>",
		"<http://www.w3.org/1999/02/22-rdf-syntax-ns#type>",
		"<http://dbpedia.org/ontology/isPartOf>",
		"<http://dbpedia.org/ontology/country>",
		"<http://dbpedia.org/ontology/timeZone>",
		"<http://dbpedia.org/ontology/type>",
		"<http://dbpedia.org/ontology/region>",
		"<http://dbpedia.org/ontology/province>",
		"<http://dbpedia.org/ontology/leaderName>",
		"<http://dbpedia.org/ontology/saint>",
		"<http://dbpedia.org/ontology/neighboringMunicipality>",
		"<http://dbpedia.org/ontology/district>",
		"<http://dbpedia.org/ontology/governmentType>",
		"<http://dbpedia.org/ontology/daylightSavingTimeZone>",
		"<http://dbpedia.org/ontology/frazioni>",
		"<http://dbpedia.org/ontology/state>",
		"<http://dbpedia.org/ontology/leaderParty>",
		"<http://dbpedia.org/ontology/part>",
		"<http://dbpedia.org/ontology/twinCity>"
		);
	
// DBpeida inbound properties
final static List<String> includeInboundPropertyList_dbpedia = Arrays.asList(
		"<http://dbpedia.org/ontology/birthPlace>",
		"<http://dbpedia.org/ontology/location>",
		"<http://dbpedia.org/ontology/deathPlace>",
		"<http://dbpedia.org/ontology/city>",
		"<http://dbpedia.org/ontology/hometown>",
		"<http://dbpedia.org/ontology/recordedIn>",
		"<http://dbpedia.org/ontology/residence>",
		"<http://dbpedia.org/ontology/isPartOf>",
		"<http://dbpedia.org/ontology/headquarter>",
		"<http://dbpedia.org/ontology/locationCity>",
		"<http://dbpedia.org/ontology/routeJunction>",
		"<http://dbpedia.org/ontology/broadcastArea>",
		"<http://dbpedia.org/ontology/builder>",
		"<http://dbpedia.org/ontology/routeStart>",
		"<http://dbpedia.org/ontology/nearestCity>",
		"<http://dbpedia.org/ontology/routeEnd>",
		"<http://dbpedia.org/ontology/ground>",
		"<http://dbpedia.org/ontology/foundationPlace>",
		"<http://dbpedia.org/ontology/assembly>",
		"<http://dbpedia.org/ontology/restingPlace>",
		"<http://dbpedia.org/ontology/place>",
		"<http://dbpedia.org/ontology/district>",
		"<http://dbpedia.org/ontology/countySeat>",
		"<http://dbpedia.org/ontology/locatedInArea>",
		"<http://dbpedia.org/ontology/country>",
		"<http://dbpedia.org/ontology/capital>",
		"<http://dbpedia.org/ontology/region>",
		"<http://dbpedia.org/ontology/populationPlace>",
		"<http://dbpedia.org/ontology/neighboringMunicipality>",
		"<http://dbpedia.org/ontology/largestCity>",
		"<http://dbpedia.org/ontology/type>",
		"<http://dbpedia.org/ontology/garrison>",
		"<http://dbpedia.org/ontology/owner>",
		"<http://dbpedia.org/ontology/homeport>",
		"<http://dbpedia.org/ontology/part>",
		"<http://dbpedia.org/ontology/regionServed>",
		"<http://dbpedia.org/ontology/team>",
		"<http://dbpedia.org/ontology/mouthMountain>",
		"<http://dbpedia.org/ontology/mouthPlace>",
		"<http://dbpedia.org/ontology/billed>",
		"<http://dbpedia.org/ontology/campus>",
		"<http://dbpedia.org/ontology/arrondissement>",
		"<http://dbpedia.org/ontology/origin>",
		"<http://dbpedia.org/ontology/county>",
		"<http://dbpedia.org/ontology/almaMater>",
		"<http://dbpedia.org/ontology/metropolitanBorough>",
		"<http://dbpedia.org/ontology/education>",
		"<http://dbpedia.org/ontology/premierePlace>",
		"<http://dbpedia.org/ontology/training>",
		"<http://dbpedia.org/ontology/state>",
		"<http://dbpedia.org/ontology/picture>",
		"<http://dbpedia.org/ontology/localAuthority>",
		"<http://dbpedia.org/ontology/majorShrine>",
		"<http://dbpedia.org/ontology/twinCity>",
		"<http://dbpedia.org/ontology/highschool>",
		"<http://dbpedia.org/ontology/municipality>",
		"<http://dbpedia.org/ontology/operator>",
		"<http://dbpedia.org/ontology/spokenIn>",
		"<http://dbpedia.org/ontology/locationCountry>",
		"<http://dbpedia.org/ontology/administrativeDistrict>",
		"<http://dbpedia.org/ontology/nationality>",
		"<http://dbpedia.org/ontology/sourcePlace>"
		);

EXAMPLE 3

public static void main(String[] args) {
	
	// DBpedia settings - without giving prefix list, using property patterns instead
	// it will filter properties which start with ""http://dbpedia.org/ontology"
	ResourceSimilarityMeasure rsmForDBpedia = new ResourceSimilarityMeasure(PropertyRestriction.SamePropertyPath,
						     "http://dbpedia.org/sparql", null, "http://dbpedia.org/ontology/", 
						     null, null, null, null);	
	System.out.println(
	rsmForDBpedia.getSimilarity("<http://dbpedia.org/resource/Hong_Kong>", "<http://dbpedia.org/resource/Singapore>", 2));
	
}

PARAMETERS

  • P1: Use one of "PropertyRestriction.SamePropertyPath" or "PropertyRestriction.DifferentPropertyPath", "SamePropertyPath" denotes considering paths with the same propery, e.g., Hong_Kong->p1->?<-p1<-Singapore, Hong_Kong<-p1<-?->p1->Singapore. On the other hand, "DifferentPropertyPath" denotes considering paths with the differnt/same propery, e.g., Hong_Kong->p2->?<-p1<-Singapore, Hong_Kong<-p2<-?->p1->Singapore.
  • P2: SPARQL Endpoint
  • P3: String for prefix list if any
  • P4: Property filtering pattern (See Example 3)
  • P5: Inbound property list
  • P6: Outbound property list
  • P7: Additional property list. This can be used with P4. For example, after defining property filtering pattern, e.g., "http://dbpedia.org/ontology/", and you can define this list (e.g., "http://purl.org/dc/terms/subject") to add more properties for consideration.
  • P8: Exclude property list. Similary to P7, define the list to exclude some properties from defined property filtering pattern.

USING HDT FOR RESIM

HDT (http://www.rdfhdt.org/) (Header, Dictionary, Triples) is a compact data structure and binary serialization format for RDF that keeps big datasets compressed to save space while maintaining search and browse operations without prior decompression. The RESIMHDT.jar provides the RESIM implementation on top of hdt format of DBpedia etc., which has been used in the original paper [2]. If you need many pairs of calculations, this might be more suitable for you as it does the calcualtion on local hdt file of DBpedia or other Linked Data. This implementation has following requriements:

  • converted hdt file of DBpedia, which can be downloaded from http://www.rdfhdt.org/
  • hdt related libraries
  • Java 1.7

EXAMPLE 4

public static void main(String[] args) throws IOException {
	
	List<String> property_list = ResourceRestrictionConfiguration.property_list;	// Property list for consideration
	List<String> excluding_property_list = ResourceRestrictionConfiguration.exclude_property_list;	// excluding property list while considering all properties
	
	/* Load DBpedia hdt file */
	HDT hdt = HDTManager.mapIndexedHDT("/Users/guangyuan/Documents/workspace02/PhDProject/dataset/DBpediaHDT/DBPedia-3.9-en.hdt", null); // Load HDT file
	System.out.println("Finished initializing HDT...");
	
	/* Initialize Resim measure */
	RESIMSimilarityCalculator resim = new RESIMSimilarityCalculator(hdt, property_list, excluding_property_list);
	
	/* Calculate similarity */
	double sim = resim.getSimWithGlobalNormalization("http://dbpedia.org/resource/Demi_Lovato", "http://dbpedia.org/resource/Lady_Gaga");
	System.out.println("similarity: " + sim);
	
}

REFENRECES

  1. Computing the Semantic Similarity of Resources in DBpedia for Recommendation Purposes, Guangyuan Piao, Safina showkat Ara, John G. Breslin 5th Joint International Semantic Technology Conference, Yichang, China, 2015 [PDF]
  2. Measuring Semantic Similarity for Linked Open Data-enabled Recommender Systems, Guangyuan Piao and John G. Breslin, The 31st ACM/SIGAPP Symposium on Applied Computing, Pisa, Italy, 2016 [PDF]
  3. Exploiting the Semantic Similarity of Interests in a Semantic Interest Graph for Social Recommendations, Guangyuan Piao, The 31st ACM/SIGAPP Symposium on Applied Computing, Pisa, Italy, 2016

resim's People

Contributors

parklize avatar

Stargazers

avatar avatar avatar avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.