Task22 - Revision history

Kolflow at 15:52, 19 February 2011

2011-02-19T15:52:58Z

← Older revision		Revision as of 15:52, 19 February 2011
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	\| no=2.2		\| no=2.2
	\| 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 conceptualisation 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::Task23]] and [[Preceeding::Task24]] 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 uses formal concept analysis to build a conceptualisation of the domain from raw texts. After validation by experts, this conceptualisation 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. 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::Task23]] and [[Preceeding::Task24]] will manage.
	Task22 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.		Task22 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.
	}}		}}

Kolflow at 15:52, 19 February 2011

2011-02-19T15:52:11Z

← Older revision		Revision as of 15:52, 19 February 2011
Line 3:		Line 3:
	\| no=2.2		\| no=2.2
	\| 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 [[Preceeding::Task23]] and [[Preceeding::Task24]] 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 conceptualisation 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::Task23]] and [[Preceeding::Task24]] will manage.
	Task22 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.		Task22 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.
	}}		}}

Desmontils-e at 17:41, 6 February 2011

2011-02-06T17:41:38Z

← Older revision		Revision as of 17:41, 6 February 2011
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	\| 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::Task23]] and [[Preceeding::Task24]] 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::Task23]] and [[Preceeding::Task24]] will manage.
	Task22 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.		Task22 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 [[D22]].~~
	}}		}}

Desmontils-e at 21:48, 5 February 2011

2011-02-05T21:48:56Z

← Older revision		Revision as of 21:48, 5 February 2011
Line 3:		Line 3:
	\| no=2.2		\| no=2.2
	\| 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 [[Preceeding::~~T23~~]] and [[Preceeding::~~T24~~]] 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::Task23]] and [[Preceeding::Task24]] 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.	+	Task22 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 [[D22]].
	}}		}}

Desmontils-e at 21:47, 5 February 2011

2011-02-05T21:47:42Z

← Older revision		Revision as of 21:47, 5 February 2011
Line 3:		Line 3:
	\| no=2.2		\| no=2.2
	\| 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.
	}}		}}

Desmontils-e: Created page with "{{Sub-task | main=Task2 | no=2.2 | title=Formal methods for knowledge extraction. | description=This task aims at defining a continuous process of knowledge extraction which uses..."

2011-02-05T07:43:26Z

Created page with "{{Sub-task | main=Task2 | no=2.2 | title=Formal methods for knowledge extraction. | description=This task aims at defining a continuous process of knowledge extraction which uses..."

New page

{{Sub-task
| main=Task2
| no=2.2
| 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.
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.
}}