S. Ferré.
Complete and Incomplete Knowledge in Logical Information Systems.
In S. Benferhat and P. Besnard, editors,
Symbolic and Quantitative Approaches to Reasoning with Uncertainty,
LNCS 2143,
pages 782-791,
2001.
Springer.
[PDF]
[POSTSCRIPT]
Keyword(s): information system,
complete and incomplete knowledge,
all i know,
modal logic.
Abstract:
We present a generalization of logic All I Know by presenting it as an extension of standard modal logics. We study how this logic can be used to represent complete and incomplete knowledge in Logical Information Systems. In these information systems, a knowledge base is a collection of objects (e.g., files, bibliographical items) described in the same logic as used for expressing queries. We show that usual All I Know (transitive and euclidean accessibility relation) is convenient for representing complete knowledge, but not for incomplete knowledge. For this, we use \emph{serial} All I Know (serial accessibility relation). |
@inproceedings{Fer2001,
author = {Ferré, S.},
title = {Complete and Incomplete Knowledge in Logical Information Systems},
booktitle = {Symbolic and Quantitative Approaches to Reasoning with Uncertainty},
pages = {782--791},
year = {2001},
editor = {S. Benferhat and P. Besnard},
series = {LNCS 2143},
publisher = {Springer},
ps = {http://www.irisa.fr/LIS/ferre/papers/ecsqaru2001.ps.gz},
pdf = {http://www.irisa.fr/LIS/ferre/papers/ecsqaru2001.pdf},
abstract = {We present a generalization of logic All I Know by presenting it as an extension of standard modal logics. We study how this logic can be used to represent complete and incomplete knowledge in Logical Information Systems. In these information systems, a knowledge base is a collection of objects (e.g., files, bibliographical items) described in the same logic as used for expressing queries. We show that usual All I Know (transitive and euclidean accessibility relation) is convenient for representing complete knowledge, but not for incomplete knowledge. For this, we use \emph{serial} All I Know (serial accessibility relation).},
keywords = {information system, complete and incomplete knowledge, all i know, modal logic},
}
S. Ferré and O. Ridoux.
Searching for Objects and Properties with Logical Concept Analysis.
In H. S. Delugach and G. Stumme, editors,
Int. Conf. Conceptual Structures,
LNCS 2120,
pages 187-201,
2001.
Springer.
[PDF]
[POSTSCRIPT]
Keyword(s): logical information system,
knowledge discovery,
navigation,
concept analysis.
Abstract:
Logical Concept Analysis is Formal Concept Analysis where logical formulas replace sets of attributes. We define a Logical Information System that combines navigation and querying for searching for objects. Places and queries are unified as formal concepts represented by logical formulas. Answers can be both extensional (objects belonging to a concept) and intensional (formulas refining a concept). Thus, all facets of navigation are formalized in terms of Logical Concept Analysis. We show that the definition of being a refinement of some concept is a specific case of Knowledge Discovery in a formal context. It can be generalized to recover more classical KD~operations like machine-learning through the computation of necessary or sufficient properties (modulo some confidence), or data-mining through association rules. |
@inproceedings{FerRid2001,
author = {Ferré, S. and Ridoux, O.},
title = {Searching for Objects and Properties with Logical Concept Analysis},
booktitle = {Int. Conf. Conceptual Structures},
pages = {187--201},
year = {2001},
editor = {H. S. Delugach and G. Stumme},
series = {LNCS 2120},
publisher = {Springer},
pdf = {http://www.irisa.fr/LIS/ferre/papers/iccs2001.pdf},
ps = {http://www.irisa.fr/LIS/ferre/papers/iccs2001.ps.gz},
abstract = {Logical Concept Analysis is Formal Concept Analysis where logical formulas replace sets of attributes. We define a Logical Information System that combines navigation and querying for searching for objects. Places and queries are unified as formal concepts represented by logical formulas. Answers can be both extensional (objects belonging to a concept) and intensional (formulas refining a concept). Thus, all facets of navigation are formalized in terms of Logical Concept Analysis. We show that the definition of being a refinement of some concept is a specific case of Knowledge Discovery in a formal context. It can be generalized to recover more classical KD~operations like machine-learning through the computation of necessary or sufficient properties (modulo some confidence), or data-mining through association rules.},
keywords = {logical information system, knowledge discovery, navigation, concept analysis},
}