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Mining fuzzy domain ontology based on
concept Vector from wikipedia category
network
IEEE/WIC/ACM international conferences on web intelligence and
intelligent agent technology, vol. 3, p.p. 249-252, Aug. 2011
Outline
 Abstract
 Introduction
 Fuzzy on tology generation
 Empirical experiments and result s
 Conclusion
 References
Abstract
 Ontology is essential in the formalization of domain
knowledge for effective human-computer interactions
(i.e.,expert-finding). Many researchers have proposed
approaches to measure the similarity between concepts by
accessing fuzzy domain ontology. However, engineering
of the construction of
 domain ontologies turns out to be labor intensive and
tedious. In this paper, we propose an approach to mine
domain concepts from Wikipedia Category Network, and
to generate the fuzzy relation based on a concept vector
extraction method to measure the relatedness between a
single term and a concept.
Abstract
 Our methodology can conceptualize domain knowledge
by mining Wikipedia Category Network. An empirical
experiment is conducted to evaluate the robustness by
using TREC dataset. Experiment results show the
constructed fuzzy domain ontology derived by proposed
approach can discover robust fuzzy domain ontologywith
satisfactory accuracy in information retrieval tasks.
Introduction
 The contribution of this paper is to propose an approach to
mine fuzzy domain ontology which contains two parts.
First , an approach is proposed to conceptualize domain
knowledge by using Wikipedia Category Network. Second,
fuzzy relation is generated to calculate the semantic
relatedness among terms, concepts, and domains.
Especially ontology-based systems can be implemented by
our fuzzy domain ontology, because domain knowledge is
categorized, and a term is mapped to the domain
knowledge by using term-domain fuzzy relation. The
underlying principles of the proposed approach will be
elaborated in the following section
Fuzzy on tology generation
Fuzzy on tology generation
 The purpose of the proposed system is to mine fuzzy
domain ontology from Wikipedia Category Network. The
fuzzy domain ontology is a representation of domain
knowledge which indicates how much a term is related to
a domain.
 Actually, Wikipedia is not only neither a tree-based
structure nor a DAG structure (Directed Acyclic Graph),
but also the directed graph with cycles. In fact, Wikipedia
permits such paradoxes as a category being its own
“grandparent” [2]. Ontology Building Stage can handle
this kind of conflict of Wikipedia Category Network. The
notations in this paper are defined as follow.
Fuzzy on tology generation
 A. Pre-Processing Stage and Wiki Mapping Stage:
 Pre-Processing Stage retrieves a set of key terms from a set of
articles, where each document belongs to one or more domains.
Wiki Mapping Stage uses the search engine to map each term to its
Wikipedia pages, and the Wikipedia pages are mapped to its
Wikipedia categories.
Fuzzy on tology generation
 B. Ontology Building Stage:
 In this stage, the fuzzy relation is generated to connect Wikipedia
categories and predefined domains. First, concept representation
finder summarizes several concepts to represent a specific domain,
each concept exists a unique concept representation which is a
Wikipedia category. Second, fuzzy relation generator has two
fuzzy relations that building relationship between Wikipedia
categories and domains. Fuzzy relation RW C is represented the
semantic relatedness of Wikipedia categories and concepts. Fuzzy
relation RC D is represented the semantic relatedness between
concepts and domain
Empirical experiments and result
Empirical experiments and result
Empirical experiments and result
Conclusion
 In this paper we propose a fuzzy domain ontology
generation methodology which uses concept vector to
traverse Wikipedia Category Network for calculating
semantic relatedness in the expert-finding system of
National Science Council of Taiwan. The proposed fuzzy
domain ontology is composed
of domain
conceptualization and term-domain fuzzy relation
generation. The proposed approach can transfer a domain
to a set concepts from Wikipedia Category Network, and
overcome Wikipedia conflict (Cyclic Graph). The
methodology can be used for ontology-based classification
problems.
References