-
O. Bedel,
S. Ferré,
and O. Ridoux.
Exploring a Geographical Dataset with GEOLIS.
In DEXA Work. Advances in Conceptual Knowledge Engineering (ACKE),
pages 540-544,
2007.
IEEE Computer Society.
[PDF]
Keyword(s): logical information system,
geographical information system,
information retrieval,
spatial logic.
Abstract: |
Geographical data are mainly structured in layers of information. However, this model of organisation is not convenient for navigation inside a dataset, and so limits geographical data exploration to querying. We think information retrieval could be made easier in GIS by the introduction of a navigation based on geographical object properties. For this purpose, we propose a prototype, GEOLIS1, which tightly combines querying and navigation in the search process of geographical data. GEOLIS relies on Logical Information Systems (LIS), which are based on Formal Concept Analysis (FCA) and logics. In this paper, we detail data organisation and navigation process in GEOLIS. We also present the results of an experimentation led on a real dataset. |
@InProceedings{BedFerRid2007a,
author = {O. Bedel and S. Ferré and O. Ridoux},
title = {Exploring a Geographical Dataset with {GEOLIS}},
booktitle = {DEXA Work. Advances in Conceptual Knowledge Engineering ({ACKE})},
year = {2007},
pages = {540--544},
publisher = {IEEE Computer Society},
pdf = {http://www.irisa.fr/LIS/ferre/papers/acke2007.pdf},
keywords = {logical information system, geographical information system, information retrieval, spatial logic},
abstract = {Geographical data are mainly structured in layers of information. However, this model of organisation is not convenient for navigation inside a dataset, and so limits geographical data exploration to querying. We think information retrieval could be made easier in GIS by the introduction of a navigation based on geographical object properties. For this purpose, we propose a prototype, GEOLIS1, which tightly combines querying and navigation in the search process of geographical data. GEOLIS relies on Logical Information Systems (LIS), which are based on Formal Concept Analysis (FCA) and logics. In this paper, we detail data organisation and navigation process in GEOLIS. We also present the results of an experimentation led on a real dataset.},
}
-
P. Cellier,
S. Ferré,
O. Ridoux,
and M. Ducassé.
A Parameterized Algorithm for Exploring Concept Lattices.
In S.O. Kuznetsov and S. Schmidt, editors,
Int. Conf. Formal Concept Analysis,
LNCS 4390,
2007.
Springer.
[PDF]
Keyword(s): taxonomy,
algorithm,
concept analysis.
Abstract: |
Formal Concept Analysis (FCA) is a natural framework for learning from positive and negative examples. Indeed, learning from examples results in sets of frequent concepts whose extent contains only these examples. In terms of association rules, the above learning strategy can be seen as searching the premises of exact rules where the consequence is fixed. In its most classical setting, FCA considers attributes as a non-ordered set. When attributes of the context are ordered, Conceptual Scaling allows the related taxonomy to be taken into account by producing a context completed with all attributes deduced from the taxonomy. The drawback, however, is that concept intents contain redundant information. In this article, we propose a parameterized generalization of a previously proposed algorithm, in order to learn rules in the presence of a taxonomy. The taxonomy is taken into account during the computation so as to remove all redundancies from intents. Simply changing one component, this parameterized algorithm can compute various kinds of concept-based rules. We present instantiations of the parameterized algorithm for learning positive and negative rules. |
@inproceedings{CFRD2007,
author = {Cellier, P. and Ferré, S. and Ridoux, O. and Ducassé, M.},
title = {A Parameterized Algorithm for Exploring Concept Lattices},
booktitle = {Int. Conf. Formal Concept Analysis},
year = {2007},
editor = {S.O. Kuznetsov and S. Schmidt},
series = {LNCS 4390},
publisher = {Springer},
pdf = {http://www.irisa.fr/LIS/ferre/papers/icfca2007-peggy.pdf},
keywords = {taxonomy, algorithm, concept analysis},
abstract = {Formal Concept Analysis (FCA) is a natural framework for learning from positive and negative examples. Indeed, learning from examples results in sets of frequent concepts whose extent contains only these examples. In terms of association rules, the above learning strategy can be seen as searching the premises of exact rules where the consequence is fixed. In its most classical setting, FCA considers attributes as a non-ordered set. When attributes of the context are ordered, Conceptual Scaling allows the related taxonomy to be taken into account by producing a context completed with all attributes deduced from the taxonomy. The drawback, however, is that concept intents contain redundant information. In this article, we propose a parameterized generalization of a previously proposed algorithm, in order to learn rules in the presence of a taxonomy. The taxonomy is taken into account during the computation so as to remove all redundancies from intents. Simply changing one component, this parameterized algorithm can compute various kinds of concept-based rules. We present instantiations of the parameterized algorithm for learning positive and negative rules.},
}
-
S. Ferré.
CAMELIS: Organizing and Browsing a Personal Photo Collection with a Logical Information System.
In J. Diatta,
P. Eklund,
and M. Liquière, editors,
Int. Conf. Concept Lattices and Their Applications,
volume 331 of CEUR Workshop Proceedings ISSN 1613-0073,
pages 112-123,
2007.
[PDF]
Keyword(s): logical information system,
photo collection,
organization,
information retrieval.
Abstract: |
Since the arrival of digital cameras, many people are faced to the challenge of organizing and retrieving the overwhelming flow of photos their life produces. Most people put no metadata on their photos, and we believe this is because existing tools make a very limited use of them. We present a tool, Camelis, that offers users with an organization of photos that is dynamically computed from the metadata, making worthwhile the effort to produce it. Camelis is designed along the lines of Logical Information Systems (LIS), which are founded on logical concept analysis. Hence, (1) an expressive language can be used to describe photos and query the collection, (2) manual and automatic metadata can be smoothly integrated, and (3) expressive querying and flexible navigation can be mixed in a same search and in any order. This presentation is illustrated by experiences on a real collection of more than 5000 photos. |
@InProceedings{Fer2007b,
author = {S. Ferré},
title = {{CAMELIS}: Organizing and Browsing a Personal Photo Collection with a Logical Information System},
booktitle = {Int. Conf. Concept Lattices and Their Applications},
year = {2007},
pages = {112--123},
editor = {J. Diatta and P. Eklund and M. Liquière},
series = {CEUR Workshop Proceedings ISSN 1613-0073},
volume = {331},
pdf = {http://www.irisa.fr/LIS/ferre/papers/cla2007.pdf},
keywords = {logical information system, photo collection, organization, information retrieval},
abstract = {Since the arrival of digital cameras, many people are faced to the challenge of organizing and retrieving the overwhelming flow of photos their life produces. Most people put no metadata on their photos, and we believe this is because existing tools make a very limited use of them. We present a tool, Camelis, that offers users with an organization of photos that is dynamically computed from the metadata, making worthwhile the effort to produce it. Camelis is designed along the lines of Logical Information Systems (LIS), which are founded on logical concept analysis. Hence, (1) an expressive language can be used to describe photos and query the collection, (2) manual and automatic metadata can be smoothly integrated, and (3) expressive querying and flexible navigation can be mixed in a same search and in any order. This presentation is illustrated by experiences on a real collection of more than 5000 photos.},
}
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S. Ferré.
The Efficient Computation of Complete and Concise Substring Scales with Suffix Trees.
In S.O. Kuznetsov and S. Schmidt, editors,
Int. Conf. Formal Concept Analysis,
LNCS 4390,
2007.
Springer.
[PDF]
Keyword(s): suffix tree,
string,
logic,
concept analysis.
Abstract: |
Strings are an important part of most real application multi-valued contexts. Their conceptual treatment requires the definition of substring scales, i.e., sets of relevant substrings, so as to form informative concepts. However these scales are either defined by hand, or derived in a context-unaware manner (e.g., all words occuring in string values). We present an efficient algorithm based on suffix trees that produces complete and concise substring scales. Completeness ensures that every possible concept is formed, like when considering the scale of all substrings. Conciseness ensures the number of scale attributes (substrings) is less than the cumulated size of all string values. This algorithm is integrated in Camelis, and illustrated on the set of all ICCS paper titles. |
@inproceedings{Fer2007a,
author = {Ferré, S.},
title = {The Efficient Computation of Complete and Concise Substring Scales with Suffix Trees},
booktitle = {Int. Conf. Formal Concept Analysis},
year = {2007},
editor = {S.O. Kuznetsov and S. Schmidt},
series = {LNCS 4390},
publisher = {Springer},
pdf = {http://www.irisa.fr/LIS/ferre/papers/icfca2007.pdf},
keywords = {suffix tree, string, logic, concept analysis},
abstract = {Strings are an important part of most real application multi-valued contexts. Their conceptual treatment requires the definition of substring scales, i.e., sets of relevant substrings, so as to form informative concepts. However these scales are either defined by hand, or derived in a context-unaware manner (e.g., all words occuring in string values). We present an efficient algorithm based on suffix trees that produces complete and concise substring scales. Completeness ensures that every possible concept is formed, like when considering the scale of all substrings. Conciseness ensures the number of scale attributes (substrings) is less than the cumulated size of all string values. This algorithm is integrated in Camelis, and illustrated on the set of all ICCS paper titles.},
}
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S. Ferré and O. Ridoux.
Logical Information Systems: from Taxonomies to Logics.
In DEXA Work. Dynamic Taxonomies and Faceted Search (FIND),
pages 212-216,
2007.
IEEE Computer Society.
[PDF]
Keyword(s): logical information system,
taxonomy,
logic.
Abstract: |
Dynamic taxonomies have been proposed as a solution for combining querying and navigation, offering both expressivity and interactivity. Navigation is based on the filtering of a multidimensional taxonomy w.r.t. query answers, which helps users to focus their search. We show that properties that are commonly used only in queries can be integrated in taxonomies, and hence in navigation, by the use of so-called logics. Hand-designed taxonomies and concrete domains (e.g., dates, strings) can be combined so as to form complex taxonomies. For instance, valued attributes can be handled, and different roles between documents and locations can be distinguished. Logical Information Systems (LIS) are characterized by the combination of querying and navigation, and the systematic use of logics. |
@InProceedings{FerRid2007,
author = {S. Ferré and O. Ridoux},
title = {Logical Information Systems: from Taxonomies to Logics},
booktitle = {{DEXA} Work. Dynamic Taxonomies and Faceted Search ({FIND})},
year = {2007},
pages = {212--216},
publisher = {IEEE Computer Society},
pdf = {http://www.irisa.fr/LIS/ferre/papers/find2007.pdf},
keywords = {logical information system, taxonomy, logic},
abstract = {Dynamic taxonomies have been proposed as a solution for combining querying and navigation, offering both expressivity and interactivity. Navigation is based on the filtering of a multidimensional taxonomy w.r.t. query answers, which helps users to focus their search. We show that properties that are commonly used only in queries can be integrated in taxonomies, and hence in navigation, by the use of so-called logics. Hand-designed taxonomies and concrete domains (e.g., dates, strings) can be combined so as to form complex taxonomies. For instance, valued attributes can be handled, and different roles between documents and locations can be distinguished. Logical Information Systems (LIS) are characterized by the combination of querying and navigation, and the systematic use of logics.},
}