From General Ontology to Specialized Ontology: A study based on a single author historical corpus

This paper proposes to deal with the construction of a specialized ontology as the discovery of a new knowledge structure, based on the premise that ontology is a structured knowledge. Our study integrates the following approaches: the mental lexicon approach, the Shakespeareangarden approach, and the ontologymerging as ontology-discovery approach. In particular, WordNet is used both a source of lexical knowledge and a (linguistic) ontology. SUMO (Suggested Upper Merged Ontology), on the other hand, is used as an upper ontology that provides fragments of well-structures knowledge. These two resources are compared and merged through Sinica BOW (Academia Sinica Bilingual Ontological Wordnet). The domain knowledge that we model our specialized ontology on is the collection of Su-Shi’s poems from Song dynasty. This work is chosen not only because the knowledge system is sufficiently different from the current one, but also because it is well-suited for the text-based and lexicon-driven strategy to discover knowledge structure. This study supports our text-based and lexicondriven approach as an efficient way to build a specialized ontology as well as to infer domain knowledge. Based on this result, we further outlined an architecture for a workbench for semi-automatic construction of specialized ontologies. 1 Motivation: General and Specialized Ontologies Gruber et al. (1994) described ontology as “an explicit specification of conceptualization. ” Ontologies can be used to explicitly represent structured information and support knowledge sharing and reuse. As a model for knowledge formation, the architecture of ontology critically depends on the type of knowledge to be represented. In terms of coverage, there are two contrasting types of ontology, general and specialized ontology. General Ontology is the upper ontology shared by all domains such as SUMO (Suggested Upper Merged Ontology). Specialized ontologies represent exhaustive information for certain domains, more specialized schemata must be created to make the data useful in making real world decisions. A specialized ontology may signify an ontology specific to a domain, historical period, an author etc. According to real conditions in a specific domain, reconstruction and verification of conceptual structure should be done. Another problem that arises in different space, time, and domain is knowledge processing with mismatched knowledge structure. One of the greatest challenges to the research on ontology is how to ensure both the felicity and compatibility of a new specialized ontology. Felicity here refers to the faithful and comprehensive representation of domain knowledge. Compatibility refers to the interchangeable and interpretability of the domain knowledge with regard to a shared upper ontology. In this paper, we propose that this challenge can be met when we take the creation of a specialized ontology as the merging of the segments of domain lexical knowledge to SUMO and WordNet. The mapping to SUMO ensures compatibility to an upper ontology, while the mapping to WordNet allows comprehensive representation of domain knowledge. Merging of the partially mapped ontology segments reduces the portion of knowledge representation which is missing from either prototypical ontology. 2 Research Methodology Three important attributes characterize our methodology: lexicon-driven, text-based, and ontologymerging. First, our methodology is (mental) lexicon-driven. Mental lexicon is defined as a language user’s knowledge of words. (Aitchison, 2003) The idea underlying our lexicon-driven approach is that concepts are stored in the mental lexicon and accessible through lexical access. In other words, we treat lexicon as a structured inventory of conceptual atoms. Second, we call our text-based approach a Shakespearean garden approach (Huang et al. 2004). A Shakespearean garden collects all the plants referred to in Shakespearean texts by identifying plants mentioned in the plays and sonnets. A Shakespearean garden is used to illustrate the flora of the Shakespearean England and gives scholars a context in which to interpret his work. For instance, a Shakespearean garden helps to illustrate how plants played important roles in medicine, religious, and history (Keyser, 2004). In our textbased approach, we do not actually grow the plants in a garden. In stead, we treat a collection of texts as an opus with an underlying knowledge structure. Since texts are composed of lexemes, we collect lexemes of a specific domain from the text just like plants are ‘collected’ from Shakespearean texts. Third, we take the ontology-merging as ontology-discovery approach. This approach deals with the dilemma for the construction of a new ontology. On one hand, if no existing ontology was referred to, a new ontology could only be an reinvented wheel. On the other hand, when an existing ontology was referred to, errors could be introduced through pre-conceived conceptual structure and important generalizations could be missed. To resolve the dilemma, we propose to map conceptual atoms to two (or more) reference ontologies. The merging of two ontologies leads to three possible scenarios: matched mapping, mismatched mapping, and complimentary mapping. Matched mapping simply confirms the knowledge structure. Mismatch mapping suggests that only one or neither is correct, and possibly lead to discovery of new knowledge structure. Lastly, when concepts are not attested in either ontology, we will have complimentary mappings. In this scenario, the coverage of either ontology can be increased coverage. A previous study that is perhaps most relevant to this current work was Huang et al.’s (2004) study of the ontology of Tang poetry. They segmented and classified a lexicon of 300 Tang Poems (618907 A.D.), to build a small ontology of the Tang civilization. Three domain ontologies, animals, plants, and artifact, were manually constructed by mapping the extracted words to SUMO. The study was able to draw some tentative generalizations, including that the Tang civilization was primarily land-locked and that it was fascinated with flying. The first generalization is supported by the fact that the node of marine mammals as well as the dominance of hoofed animals. The second generalization is supported by the dominant frequency of birds among vertebrates, as well as the fact that insects are the only attested invertebrates (since they are the only winged invertebrates). In short, the knowledge structure of a specialized ontology helps to form new knowledge.