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FP7 meeting - Gent - Carlos Rodríguez - April 18 WP4: Conceptual Mining from Text for Knowledge Engineering State of the Art WP Coordinators: Alfonso Valencia.

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Presentation on theme: "FP7 meeting - Gent - Carlos Rodríguez - April 18 WP4: Conceptual Mining from Text for Knowledge Engineering State of the Art WP Coordinators: Alfonso Valencia."— Presentation transcript:

1 FP7 meeting - Gent - Carlos Rodríguez - April 18 WP4: Conceptual Mining from Text for Knowledge Engineering State of the Art WP Coordinators: Alfonso Valencia Carlos Rodriguez

2 FP7 meeting - Gent - Carlos Rodríguez - April 18 Why Concept/Semantic Mining? Knowledge Acquisition Bottleneck Top-Down, manually-designed Ontologies are: sparse (non-exhaustive) shallow (not fine-grained) not mappable (to terms or other ontologies) not easily updated or customized Text-based ontologies reflect better diversity in knowledge as reflected by the literature and domain terminology

3 FP7 meeting - Gent - Carlos Rodríguez - April 18 Information for Ontology Learning

4 FP7 meeting - Gent - Carlos Rodríguez - April 18 State of the Art Methods implicit relations Corpus Distribuition Machine Learning Algorithms explicit relations Symbolic (rule and syntax-based) Hybrid, combining some or all Bootstrap the ontology-learning process using existing resources

5 FP7 meeting - Gent - Carlos Rodríguez - April 18 Meiosis Cyclin Checkpoint Interphase Nucleoplasma Division Histone Replication Chromatid Dipeptidyl Prolyl nmr Collagen-binding 17 genes PCNA CDC2 MSH2 LBR TOP2A genes ABCA5 CAT ELF2 PIM1 WNT2... Cell cycle Unknown DNA replication DNA metabolism Cell Cycle control PCNA-MSH2 The binding of PCNA to MSH2 may reflect linkage between mismatch repair and replication. LBR-CDC2 LBR undergoes mitotic phosphorylation mediated by p34(cdc2) protein kinase. Words GO codes Sentences Words Blaschke, et al., Funct. Integ. Genomics 2001 An example

6 FP7 meeting - Gent - Carlos Rodríguez - April 18 Induce rules at different linguistic levels

7 FP7 meeting - Gent - Carlos Rodríguez - April 18 Lexical- and syntax-derived relationships from text Complex relationships in CCO degradates participate_in catalyses adjacent_to agent_in What new ones can be learnt? LBR undergoes mitotic phosphorylation mediated by p34(cdc2) protein kinase. mitotic phosphorylation mediated_by protein kinase Can it be subsumed by others? Are there other subcategories?

8 FP7 meeting - Gent - Carlos Rodríguez - April 18 Beyond the State of the Art Optimal hybrid methodology for: Extracting entities Discovering relations Providing ontology-relevant information (But what and how ?) Comparing top-down with bottom-up ontologies Providing definitional information Application to CC-cancer domains (and possibly to gene regulation)

9 FP7 meeting - Gent - Carlos Rodríguez - April 18 In the context of project and other WPs… Reasoning with text-generated ontologies: competing or complementing? Reduction of lexical and semantic relationships to ontological relation inventory How to present and use Text-Mined information for ontology design (especially for database annotation)? How to curate, evaluate and compare ontologies?

10 FP7 meeting - Gent - Carlos Rodríguez - April 18 Information for Ontology Engineers New Classes (ontology) and Instances (KB) Definitions and glosses Concept usage and entity examples Terms and synonyms Hierarchical and non-hierarchical relations Possible reasoning rules

11 FP7 meeting - Gent - Carlos Rodríguez - April 18 To and Fro other WPs WPTofrom 1: CCO extension New entities, terms, definitions and relations Seeds for learning and ontology curation 2.- Ontology Engineering Integration of text-mining into ontology design methods Ontology evaluation 3.- Corpus Processing and Curation Subcorpus and term inventories Annotated corpus 5.- Knowledge Base Population New entities, terms definitions and relations Ontology evaluation and curation 6.- Reasoning New relations and inference rules from text Evaluation of mappings and reasoning


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