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SPECIFIC SEARCH OF CROWDSOURCED OPENSTREETMAP DATASET AND WIKI - PowerPoint PPT Presentation

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OGRS 2012 ONTOLOGY BASED DOMAIN SPECIFIC SEARCH OF CROWDSOURCED OPENSTREETMAP DATASET AND WIKI Prof. Stefan Keller and Michel Ott Yverdon-les-Bains, 26. October 2012 The Problem: Finding Tags in OSM OpenStreetMap (OSM) crowdsourced

  1. OGRS 2012 ONTOLOGY BASED DOMAIN SPECIFIC SEARCH OF CROWDSOURCED OPENSTREETMAP DATASET AND WIKI Prof. Stefan Keller and Michel Ott Yverdon-les-Bains, 26. October 2012

  2. The Problem: Finding Tags in OSM  OpenStreetMap (OSM)  crowdsourced (or volunteered geographic information) mapping project  uses an extensible Entity/Attribute/Value schema.  ‘tag’ consists of a key and a value  p.ex . “viewpoint” is defined as "tourism=viewpoint”  Problem  “schema” is changing and growing constantly ( curr. ~1500 different tags)  How to find the most relevant tags?  This talk  explains the information retrieval (IR) approach we have chosen  a prototype called TagFinder we have implemented  future challenges, like constructing thesaurus/ontology 2 Ontology Based Domain Specific Search...

  3. TagFinder in Action Find relationships Search term entered … and translations Present result list Get statistics from Taginfo 3 Ontology Based Domain Specific Search...

  4. TagFinder: Data Flow 4 Ontology Based Domain Specific Search...

  5. TagFinder: How it works Implemented (see slide before): Lookup given input string (any language) in taxonomy/thesaurus 1. 2. If input string found: Get a list of preferred key-value pairs Lookup related terms of each preferred key-value pair for one level 3. Collect statistics from Taginfo for each term 4. Clean tag list 5. Rank according to TagInfo's term statistics 6. 7. Return resulting tag list 5 Ontology Based Domain Specific Search...

  6. Related terms in OSM Wiki pages „ Related Terms“ (RT) (RT being the common „ public “ notion) 6 Ontology Based Domain Specific Search...

  7. Representation of semantics  Taxonomy  Subject/term description consisting one relationship: the broader/narrower relationship  Builds a hierarchy  Thesaurus  Extends a taxonomy  Structured vocabulary with "related term" and "preferred term" (inversely: use...) relationships, and "scote note" property  Ontology (Topic Map)  Describes "the world" with any set of types, properties, and relationship types . 7 Ontology Based Domain Specific Search...

  8. Example: SKOS encoding of a ontological ‚ concept ‘ <skos:Concept rdf:about="#castle"> <rdf:type rdf:resource="http://www.w3.org/2002/07/owl#Thing"/> <skos:prefLabel xml:lang="en">castle</skos:prefLabel> <skos:topConceptOf rdf:resource="#OSM"/> <skos:inScheme rdf:resource="#OSM"/> <skos:altLabel xml:lang="de">Chateau</skos:altLabel> <skos:altLabel xml:lang="de">Palais</skos:altLabel> <skos:altLabel xml:lang="de">Palast</skos:altLabel> <skos:altLabel xml:lang="de">Prachtbau</skos:altLabel> <skos:altLabel xml:lang="de">Schloss</skos:altLabel> <skos:broader rdf:resource="#historic"/> <skos:related rdf:resource="#citadel"/> <skos:related rdf:resource="#fortification"/> <skos:related rdf:resource="#fortress"/> <skos:related rdf:resource="#mansion"/> <skos:related rdf:resource="#palace"/> <skos:related rdf:resource="#peel"/> <skos:related rdf:resource="#stronghold"/> </skos:Concept> (http://openpoimap.ch/resources/osm_skos.xml ) 8 Ontology Based Domain Specific Search...

  9. Possible future work Linguistic preprocessing:  Detect search term language  Serves also as (spatial) filter to disambiguate terms Example: “Atelier” is either “garage/repair shop” ( fr ) or an “arts studio” (de)   Word stemming, fuzzy string matching  Lookup online word translation list But the biggest challenge is … 9 Ontology Based Domain Specific Search...

  10. Challenge How to extract and crowdsource a taxonomy (thesaurus/ontology ) … understandable, and sustainable? Given Pareto‘s 80/20 rule and besides Related Terms… 10 Ontology Based Domain Specific Search...

  11. Contact THANK YOU! www.openpoimap.ch/tagfinder Stefan Keller & Michel Ott University of Applied Sciences Rapperswil (HSR) CH-8640 Rapperswil (Switzerland) sfkeller@hsr.ch 11 Ontology Based Domain Specific Search...

  12. Appendix: From Thesaurus to Ontology … Source: Norman Hasany, Natural Language Processng, http://de.scribd.com/doc/7292913/14/ 12 Ontology Based Domain Specific Search...

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