From Kolflow Project
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| | | title=Continuous extraction, edition, and annotation | | | title=Continuous extraction, edition, and annotation |
| | | activities=extracting knowledge units from texts using data mining | | | activities=extracting knowledge units from texts using data mining |
| - | | description= | + | | description=This task aims at proposing a process where in extracting knowledge from different kinds of sources. The challenge in this task is that at any time, automatic (and formal) methods extracting knowledge could be invoked and run in accordance with already stored knowledge. In the other way, human should be able to correct or to enrich, at any time, the ontology. Usually, humans operate after automatic knowledge extraction systems so that they have no formal constraints in operations they perform. |
| | + | Knowledge extraction is an iterative and interactive process involving several steps. Interaction is usually described as evaluation, where experts are asked to interpret and validate pattern extracted by data mining algorithms. In fact, extracting information from texts is closer to trial and error process than to a one-shot process and expert interaction involves as well to look back at the previous step, such as data selection, data preprocessing to “tune” data. This look back will be perform thanks to the annotation process. The annotation process guides the construction of the ontology and the ontology guides the annotation process. |
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| | Participants : | | Participants : |
| - | * [[Task participant::GDD;43]] | + | * [[Task participant::GDD;47]] |
| - | * [[Task participant::Edelweiss;29]] | + | * [[Task participant::Edelweiss;3]] |
| - | * [[Task participant::Orpailleur;14]] | + | * [[Task participant::Orpailleur;49]] |
| - | * [[Task participant::Silex;14]] | + | * [[Task participant::Silex;1]] |
Revision as of 07:24, 5 February 2011
Title : Continuous extraction, edition, and annotation
Code : 2
Responsible : Orpailleur
Activities : extracting knowledge units from texts using data mining
Start Date :
End Date :
Objectives : This task aims at proposing a process where in extracting knowledge from different kinds of sources. The challenge in this task is that at any time, automatic (and formal) methods extracting knowledge could be invoked and run in accordance with already stored knowledge. In the other way, human should be able to correct or to enrich, at any time, the ontology. Usually, humans operate after automatic knowledge extraction systems so that they have no formal constraints in operations they perform.
Knowledge extraction is an iterative and interactive process involving several steps. Interaction is usually described as evaluation, where experts are asked to interpret and validate pattern extracted by data mining algorithms. In fact, extracting information from texts is closer to trial and error process than to a one-shot process and expert interaction involves as well to look back at the previous step, such as data selection, data preprocessing to “tune” data. This look back will be perform thanks to the annotation process. The annotation process guides the construction of the ontology and the ontology guides the annotation process.
Success criteria :
Risks :
Deliverables :
|
description |
Feb2011+months |
| D21 |
Building a corpus for experimenting continuous knowledge extraction. |
66 |
| D22 |
Integrating a knowledge extraction system from texts in a semantic wiki. methodology, modules, and experiments. |
1212 |
| D23 |
Specification of a continuous knowledge extraction system |
1818 |
| D24 |
Dynamic semantic annotation in a semantic wiki: definitions and specifications |
3636 |
| D25 |
Continuous extraction, edition and annotation in a semantic wiki ; report advances on this task at the end of the project. |
3636 |
Sub-tasks :
|
title |
| Task21 |
Collecting data |
| Task22 |
Formal methods for knowledge extraction. |
| Task23 |
Continuous extraction of knowledge. |
| Task24 |
Semantic Annotation. |
Participants :
