From Kolflow Project
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| | | title=Formal methods for knowledge extraction. | | | title=Formal methods for knowledge extraction. |
| - | | description=This task aims at defining a continuous process of knowledge extraction which uses recent works we carried out in Orpailleur on knowledge extraction. Indeed, Bendaoud’s thesis[18] uses formal concept analysis to build a conceptualisation of the domain from raw texts. After validation by experts, this conceptual- isation is transformed in an ontology encoded in description logics. A prototype implements this methodology that was tested in astronomy, in microbiology and some attempts in the Taaable project for building a cook ontology [16]. The strength of such a formal approach is that building an ontology is now a process guided by the corpus less time consuming than a full-manual process. Subjectivity in building the ontology is also reduced with such a process. However, this work suffers from several weaknesses that the following subtasks T2.3 and T2.4 will manage. | + | | description=This task aims at defining a continuous process of knowledge extraction which uses recent works we carried out in Orpailleur on knowledge extraction. Indeed, Bendaoud’s thesis[18] uses formal concept analysis to build a conceptualisation of the domain from raw texts. After validation by experts, this conceptual- isation is transformed in an ontology encoded in description logics. A prototype implements this methodology that was tested in astronomy, in microbiology and some attempts in the Taaable project for building a cook ontology [16]. The strength of such a formal approach is that building an ontology is now a process guided by the corpus less time consuming than a full-manual process. Subjectivity in building the ontology is also reduced with such a process. However, this work suffers from several weaknesses that the following subtasks [[Preceeding::T23]] and [[Preceeding::T24]] will manage. |
| | T2.2 aims at integrating our prototype for building a conceptualisation from texts into a semantic wiki environment. This requires that texts are entered in the semantic wiki as resources. Natural language processing as well as formal concept analysis (FCA) will be defined as modules. And finally, results from FCA – the conceptualisation – should be encoded as the ontology in the semantic wiki. | | T2.2 aims at integrating our prototype for building a conceptualisation from texts into a semantic wiki environment. This requires that texts are entered in the semantic wiki as resources. Natural language processing as well as formal concept analysis (FCA) will be defined as modules. And finally, results from FCA – the conceptualisation – should be encoded as the ontology in the semantic wiki. |
| | Results of this tasks – methodology, modules, and experiments – will be recorded in deliverable D2.2. | | Results of this tasks – methodology, modules, and experiments – will be recorded in deliverable D2.2. |
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Revision as of 21:47, 5 February 2011
Refering task : Task2
Title : Formal methods for knowledge extraction.
Code : 2.2
Start Date :
End Date :
Description : This task aims at defining a continuous process of knowledge extraction which uses recent works we carried out in Orpailleur on knowledge extraction. Indeed, Bendaoud’s thesis[18] uses formal concept analysis to build a conceptualisation of the domain from raw texts. After validation by experts, this conceptual- isation is transformed in an ontology encoded in description logics. A prototype implements this methodology that was tested in astronomy, in microbiology and some attempts in the Taaable project for building a cook ontology [16]. The strength of such a formal approach is that building an ontology is now a process guided by the corpus less time consuming than a full-manual process. Subjectivity in building the ontology is also reduced with such a process. However, this work suffers from several weaknesses that the following subtasks T23 and T24 will manage.
T2.2 aims at integrating our prototype for building a conceptualisation from texts into a semantic wiki environment. This requires that texts are entered in the semantic wiki as resources. Natural language processing as well as formal concept analysis (FCA) will be defined as modules. And finally, results from FCA – the conceptualisation – should be encoded as the ontology in the semantic wiki.
Results of this tasks – methodology, modules, and experiments – will be recorded in deliverable D2.2.
Deliverables :
|
description |
Feb2011+months |
| D22 |
Integrating a knowledge extraction system from texts in a semantic wiki. methodology, modules, and experiments. |
1212 |
