Semantic Annotation, Search and Analysis

Transcription

1 Semantic Annotation, Search and Analysis Borislav Popov, Ontotext

2 Ontology A machine readable conceptual model a common vocabulary for sharing information machine-interpretable definitions of concepts in a domain and their relations formal representation of a set of concepts within a domain and the relationships between them

3 Conceptual Schemata and Individuals Schema(ta) the laws Classes and Properties Individuals the population Instances of classes (Alice is a Girl) Facts characteristics, relationships and interactions of individuals

4 Representation Languages and Usage RDF & OWL are being widely accepted Mostly visible through RSS, FOAF, and Linked Open Data (LOD Cloud on the right)

5 Query Languages Defining path patterns over the knowledge graph W3C recommendation is SPARQL Results are sets of nodes in the graph Example on the left defines the pattern: Classes Blog posts (and their titles) commented by people interested in the WWW conference in 2008 Properties Instance

6 Semantic Annotation (as of 2001) Alignment with respect to a conceptual model and an individual in an underlying instance base It is both Sort of meta-data and the process of creating this meta-data

7 Simple Usage: Highlight, Hyperlink, and

8 Simple Usage: Explore and Navigate

9 Identification / Identity Resolution

10 Semantic Annotation (as of 2008)

11 Cross Doc Coreference

12 Semantic Repositories provide storage, indexing, querying & automatic reasoning of structured data using ontologies as semantic schemata and dynamic data models, that can change on the fly ptop:agent mydata:ivan owl:symmetricproperty owl:inverseof owl:inverseof owl:relativeof ptop:parentof rdfs:subpropertyof owl:inverseof ptop:person rdfs:range owl:inverseof owl:inverseof ptop:childof ptop:woman mydata: Maria inferred rdf:type

13 OWLIM OWLIM is Ontotext s semantic database Handling billions of facts and configurable inference Allowing structured queries and FTS on literals Supporting extended RDF models (quadruples and quintuples) Swift OWLIM uses in-memory reasoning and query evaluation and is the fastest known RDF(S) and OWL engine Big OWLIM uses binary persistence and is the only engine proven to support non -trivial OWL inference against 12+ billion facts Lots of benchmarks on real and synthetic data sets (including LOD) are available

14 KIM Platform for semantic annotation, indexing and retrieval automatic knowledge acquisition through built-in GATE-based text mining or 3 rd party meta-data generation for other content types (e.g. multimedia) Multi-paradigm navigation and retrieval on top of: Text (FTS) with document structure and metadata restrictions Conceptual models, instance base, and facts; taking benefit of inference Co-occurrence of instances in contexts Annotation patterns Hybrid or multi-paradigm queries combining all of these

15 KIM Platform Disks WWW Intranet Existing models, taxonomies, dictionaries, thesauri, schemata O 1 O 2 O 3 3 rd party Ontology Editors Document & Meta Data Aggregator / Crawler A B C D Knowledge Base Engineering Convertors Visual Interface 3rd party App Semantic Indexing & Storing Semantic Index Multi-paradigm Search/Retrieval

16 Need Definition Natural Language Semantic Search Meaning Structured Queries Metadata; Patterns Some meaning FTS words

17 Retrieval Paradigms STRUCTURE: graph pattern search PATTERNS: predefined pattern searches; canned queries FACETS: Co-occurrence based search HYBRID: hybrid FTS, doc structure, metadata, entity lookup and co-occurrence search ANNOTATIONS: ANNIC-style Mimir-powered search over annotation patterns BOOLEAN: FTS with restrictions on doc structure and metadata ONTOLGY: conceptual model hierarchy observation

18 Retrieval: BOOLEAN Boolean operators Document structure Doc-level metadata

19 Structure Entity pattern queries over the ontology/kb graph structures

20 Patterns

21 Retrieval Paradigms: FACETS Facets of specific Class/Type Filtering as you type Co-occurrence based Selection reduces the document set and the facets contents

22 Results: Entity Sets Sets of entities matching the query Hyperlinked to their semantic descriptions Further navigation

23 Results: Documents Doc set matching the query With some metadata and snippets Hyperlink to Doc Detail

24 Results: Doc Detail, Metadata

25 Results: Doc Details: Content Navigation Hyperlinked Searched Terms & Entities

26

27 Some Applications ln.ontotext.com - small corpus of recent news with focus on people, orgs, GPEs kim.ontotext.com same type of entities but for 1.2M news fda.semanticannotation.com/exopatent drug-development patents analyzed for measurements, drugs, compounds, diseases, etc. ARIS Asset Recovery Intelligence System Explanation of the corpora, setup, IE apps, search & everything will be verbal only Demos and Hands-on now More at: