Open hpi semweb-06-part7
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Open hpi semweb-06-part7 Open hpi semweb-06-part7 Presentation Transcript

  • Semantic Web TechnologiesLecture 6: Applications in the Web of Data 07: Semantic Search Dr. Harald Sack Hasso Plattner Institute for IT Systems Engineering University of Potsdam Spring 2013 This file is licensed under the Creative Commons Attribution-NonCommercial 3.0 (CC BY-NC 3.0)
  • 2 Lecture 6: Applications in the Web of Data Open HPI - Course: Semantic Web Technologies Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  • 3 07 - Semantic SearchOpen HPI - Course: Semantic Web Technologies - Lecture 6: Applications in the Web of Data Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  • 4 Meaning sender Experience receiver Context Concept symbolizes refers toExperience http://commons.wikimedia.org/wiki/User:McSmit Symbol Object stands for Armstrong Pragmatics Ogden, Richards: The Meaning of Meaning: Semantic Web Technologies , Dr. Harald Sack, Hasso Plattner Institute, University of Study of the Influence of Language upon Thought and of the Science of Symbolism (1923) A Potsdam
  • Arms tron gSemantic Web Technologies , Dr. Harald Sack, Hasso Plattner Institute, University of Potsdam
  • http://dbpedia.org/resource/Neil_Armstrong Neil Armstrong Entities is a is a Ontologies same asKosmonaut Astronaut Person subClassOf is NOT a Science Occupation subClassOf has an Employment
  • Classical Information Retrieval files of records7 Set of Documents (acc. to Salton,G., McGill, M.J.: Introduction to Modern Information Retrieval. McGraw-Hill, New York 1983) Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  • Classical Information Retrieval Information requests files of records7 Set of Queries Set of Documents (acc. to Salton,G., McGill, M.J.: Introduction to Modern Information Retrieval. McGraw-Hill, New York 1983) Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  • Classical Information Retrieval Information requests files of records7 Set of Queries Set of Documents similarity Query indexing Formulation indexing language (acc. to Salton,G., McGill, M.J.: Introduction to Modern Information Retrieval. McGraw-Hill, New York 1983) Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  • Classical Information Retrieval (simplified version) Set of documents8 „search“ ? searching, vb. , in allen ger n sprachen bezeugt: got.sokjan, ags. sēcan, as. sokian, an. Soekj search term(s) keywords [Bd. 20, Sp. 835] sēza, ahd. suohhan. aus idg. sprachen steht am nächsten lat. sāgiospüre, air. saigim gehe search query einer sache nach, suche; zur weiteren verwandtschaft vgl. Walde-Pokorny 2, 449. der umlaut des stammvokals erscheint im nd., er wird im md. verzeichnet vonCrecelius oberhess. wb. 827; Spiess henneb. id. 248; Hertel Thüringen240; Gerbet Vogtland 425 und auf kolonialem boden bei Schröerdeutsche mundarten des ungrischen berglandes 225. neben eigentlichem suchen einer sache nachspüren, sich bemühen, sie aufzufinden (dann auch jemanden aufsuchen, ihn bedrohen, angreifen) steht search index eine reich bezeugte bedeutungsgruppe mehr Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  • Evaluation of Information Retrieval Systems9 |R∩P| Recall = |R| |R∩P| Precision = relevant documents that have been retrieved |P| (1+α)⋅(Recall ⋅ Precision ) Fα= α⋅(Recall + Precision ) P R relevant documents retrieved documents Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  • Semantic Search (One of many Definitions...)10 • Annotation of (text-based) metadata with semantic entities • Entity-based Information Retrieval • Make use of semantic relations, as e.g. content-based similarities of relationships • Interoperable metadata via semantic annotations • for content-based description • for structural / technical description (Multimedia Ontologies) Overall Goal: Quantitative and qualitative improvement of Information Retrieval Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  • Semantic Search Semantic metadata enable improvement of traditional keyword- based retrieval by(1) Query String Extension/Refinement enables more precise or more complete search results(2) Cross Referencing enables to complement search results with additional associated or similar information(3) Exploratory Search enables visualization and navigation of the search space(4) Reasoning enables to complement search results with implicitly given information Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  • Semantic Search Query String Extension12 • Keyword-based search does not deliver all search results that are relevant for a query, because synonyms and metaphors might describe the queried content. • Extension of the original query string (Query Extension) • from dictionaries and thesauri • extend query with synonyms, hyponyms, etc. • from domain ontologies • extend query with meronyms, related concepts, etc. Original query string: Bank possible extensions: Bank ∨ depository financial institution ∨ credit union ∨ acquirer ∨ federal reserve ∨ ... increase recall Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  • Semantic Search Query String Refinement13 • Keyword-based search does also deliver search results that are not relevant for a query, because query terms and document terms might be ambiguous. • Refinement of the original query string (Query Refinement) • from dictionaries and thesauri • disambiguate polysemic terms with hypernyms • from domain ontologies • disambiguate polysemic terms with holonyms Original query string: Bank possible refinements: (1) Bank ∧ financial institution (2) Bank ∧ incline ∧ slope ∧ side (3) Bank ∧ container (4) Bank ∧ deposit ∧ repository increase precision Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  • Semantic Search Cross Referencing14 • Provide search results that do not literally contain the query string but are closely related to the query by content • Apply domain ontologies for determining related concepts • Apply statistical analysis of large (text) document corpora dbprop:mission dbpedia:Michael_Collins dbpedia:Apollo_11 dbprop:mission dbprop:mission Neil Armstrong dbpedia:Neil_Armstrong dbpedia:Buzz_Aldrin NER query string Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  • Semantic Search Exploratory Search15 • Provide additional search results that do not necessarely contain 95 the query string but are related to the query by content or also are related to the search results achieved by the direct query • Apply domain ontologies and heuristics to determine the relevance of facts dcterms:subject category:Apollo_program dbpedia:Apollo_11 dcterms:subject dbpedia-owl:mission dbpedia:Apollo_13 rdf:type dbpedia:Neil_Armstrong yago:Space_accidents_and_incidents rdf:type dbpedia:Space_Shuttle_Challenger Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  • Semantic Search Reasoning16 • Provide additional search results (and information) that do not 95 necessarely contain the query string but are related to the query by content, whereby the relation may not be a direct one, but can be derived via entailment. • Apply domain ontologies, reasoning algorithms and heuristics to find new facts and determine the relevance of facts Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  • Semantic Search Reasoning17 95 Example: query string= Neil Armstrong (Hard) questions to solve via reasoning: • Will there be the Moon or documents about the Moon in the search results? • How is Neil Armstrong related to the Moon? (is he?) • Was Neil Armstrong (really) on the Moon? • ... category:Missions_to_the_Moon dcterms:subject dcterms:subject category:Exploration_of_the_Moon dbpedia:Apollo_11 skos:broader skos:broader dbpedia-owl:mission category:Spaceflight dbpedia:Neil_Armstrong category:Moon dcterms:subject skos:broader dbpedia:Moon category:Animals_in_Space Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
  • 18 08 - Exploratory Semantic Search Open HPI - Course: Semantic Web Technologies - Lecture 6: Applications in the Web of Data Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam