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Semantic Search Tutorial Introduction

Semantic Search Tutorial Introduction. Miriam Fernandez | KMI, Open University, UK Thanh Tran | Institute AIFB, KIT, DE Peter Mika| Yahoo Research, Spain. Search Document Retrieval vs. Data Retrieval. Differences of search technologies Representation of the user need ( query model )

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Semantic Search Tutorial Introduction

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  1. Semantic Search TutorialIntroduction Miriam Fernandez | KMI, Open University, UKThanh Tran | Institute AIFB, KIT, DEPeter Mika| Yahoo Research, Spain

  2. Search Document Retrieval vs. Data Retrieval • Differences of search technologies • Representation of the user need (query model) • Representation of the underlying resources (data model) and • Matching technique • Information Retrieval (IR) support the retrieval of documents (document retrieval) • Representation based on lightweight syntax-centric models • Work well for topical search • Not so well for more complex information needs • Database (DB) and Knowledge-based Systems (KB) deliver more precise answers (data retrieval) • More expressive models • Allow for complex queries • Retrieve concrete answers that precisely match queries

  3. Semantic Search • Semantic search can be seen as a retrieval paradigm, that is • Centered on the use of semantics • Precisely: incorporates semantics entailed in query & resources into the matching process • Broadly: incorporates the semantics into some steps throughout the process • Wide range of semantic search systems • Employ semantic models of varying expressivity at different steps

  4. Semantic Models • Semantics is concerned with the meaning of the resources made available for search • Meaning is established through semantic models • Linguistic model • Model relationships at the world level • Taxonomies, thesauri • Conceptual model (“explicit”) • Mole relationships between syntactic elements denoting entities of universe of discourse • Interpretation: mapping of syntactic elements to universe of discourse • Expressivity • Number & kinds of modeling constructs • Formality • Interpretations are computable

  5. Categories of Semantic Search • DB and KB systems belong to “heavyweight semantic search systems” • Explicit and formal models of semantics, e.g. • Entity Relationship schemas, and • Knowledge models available in RDF(S) and OWL • Mainly semantic data retrieval systems • Semantics-based IR systems belong “lightweight semantic search systems” • Lightweight semantic models, e.g. taxonomies and thesauri • Semantic data (RDF) embedded in or associated with documents • Semantic document retrieval systems

  6. Semantic Search – a Process View Knowledge Representation Semantic Models Resources Documents DocumentRepresentation

  7. Convergence of DB & KB & IR on the Web • Trend: increased availability of structured and semantic data • Data Web Search • Semantic data retrieval & inferences in larger Web scenario • Differences: scale, heterogeneity, quality, vague information needs • Adopt IR technologies for scalability, to deal with quality problem of Web data • Document Web Search • Database and Semantic Web technologies are applied to the IR problem to exploit richly structured and highly expressive data • Examples: Yahoo, Google, Bing Facebook • Convergence in terms of the • Data and techniques

  8. Semantic Search Systems Semantic search systems might combine a range of techniques, ranging from statistics-based IR methods for ranking, database methods for efficient indexing and query processing, up to complex reasoning techniques for making inferences!

  9. Agenda • 9am: Introduction • 9:15am: Representation of the Serch Space ---------------------------------------------------------------------- • 10:00am: Coffee Break • 10:15am: Data Preprocessing: Indexing & Crawling • 11:30am: Query Processing ---------------------------------------------------------------------- • 12:30pm: Lunch Break • 2:00pm: Query Processing • 2:20pm: Demo • 2:30pm: Ranking ---------------------------------------------------------------------- • 3:30pm: Coffee Break • 3:45pm: Demo • 4:00pm: Result Presentation • 4:15pm: Demo • 4:30pm: Evaluation • 5:00pm: Discussion and wrap-up • 5:30pm:End

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