CONTENTS

A FORMAL CONCEPT ANALYSIS APPROACH TO ONTOLOGY SEARCH 221
can help us find the search elements in the search space by using synonyms, meronyms
and other word relations that can alone be the subject of an entire paper.
The concepts found in the previous step are, each one of them, the start point of
an ”extracted lattice”. This lattice is to be constructed in a similar manner with the
initial lattice but taking into account a concept radius. This can be seen as sort of
a threshold for a concept set extracted from the search space. Starting from a found
concept, the agent constructs a lattice by including all the concepts related to the
found concept while staying withing the boundaries given by the concept radius. The
concept radius can be any function defining types of relations between concepts and
a simple example of such a function is the ontology relations set itself.
After the lattice has been extracted from the search space around the starting
point, the agent starts integrating it in the main lattice. This can be done by means
similar to FCA-Mapping[2] but since we started the search with the concepts from
the main lattice, we already have the information regarding to what concept to link
the extracted lattice to. Each starting point can be linked to a subset of concepts
from the initial domain when they are found in the search space, and this process of
integration will be done for each one of them.
After obtaining the generated lattice, by combining the initial lattice with the
extracted ones, we can measure the degree of similarity between the initial domain
and the current ontology by analyzing the generated lattice. There are multiple
metrics we can use here, including the number of lattice concepts, the structure of
the lattice, how well connected are the concepts and how many clusters we have and
so on.
3. Related Work
Formal Concept Analysis has been mixed in the computer science field for a while
now and not without good reasons according to its strong supporters for its benefits
[11], but not until fairly recently researchers in the ontology field became interested
in its potential [13, 2]. At the moment there are applications both theoretical [10, 9]
and practical 2 that are using the power of FCA and this shows, without doubt, that
FCA has some leverage in the knowledge related fields. However, we have the string
belief that FCA has much more potential in this area as an ontology tool for tasks
like similarity[3], mapping, validation and enhancement.
References
[1] Timothy J. Everts, Sung Sik Park, and Byeong Ho Kang. Using formal concept analysis with
an incremental knowledge acquisition system for web document management.
[2] Liya Fan and Tianyuan Xiao. FCA-Mapping: A method for ontology mapping. In Proceedings
of the European Semantic Web Conference, 2007.
[3] Anna Formica. Concept similarity in formal concept analysis: An information content approach.
In Knowledge Based Systems, 2007.
[4] Suk-Hyung Hwang. A triadic approach of hierarchical classes analysis on folksonomy mining.
In IJCSNS International Journal of Computer Science and Network Security, VOL.7 No.8,
August 2007.
2 http://sourceforge.net/projects/conexp