Natural language interfaces to ontologies allow users to query the system using natural language queries.
These systems take natural language query as input and transform it to formal query language equivalent
to retrieve the desired information from ontologies. The existing natural language interfaces to ontologies
offer support for handling negation queries; however, they offer limited support for dealing with them.
This paper proposes a negation query handling engine which can handle relatively complex natural
language queries than the existing systems. The proposed engine effectively understands the intent of
the user query on the basis of a sophisticated algorithm, which is governed by a set of techniques and
transformation rules. The proposed engine was evaluated using the Mooney data set and AquaLog dataset,
and it manifested encouraging results.
The use of graphical knowledge representation formalisms with a representational vocabulary agreement of terms of conceptualization of the universe of discourse is a new high potential approach in the ontology engineering and knowledge management context. Initially, concept maps were used in the fields of education and learning. After that, it became popular in other areas due to its flexible and intuitive nature. It was also proven as a useful tool to improve communication in corporate environment. In the field of ontologies, concept maps were explored to be used to facilitate different aspects of ontology development. An essential reason behind this motivation is the structural resemblance of concept maps with the hierarchical structure of ontologies. This research aims to demonstrate quantitative evaluation of 4 different hypotheses related to the effectiveness of using concept maps for ontology conceptualization. The domain of Quran was selected for the purpose of this study and it was conducted in collaboration with the experts from the Centre of Quranic Research, Universiti Malaya, Kuala Lumpur, Malaysia. The results of the hypotheses demonstrated that concept mapping was easy to learn and implement for the majority of the participants. Most of them experienced improvement in domain knowledge regarding the vocabularies used to refer to the structure of organization of the Quran, namely Juz, Surah, Ayats, tafsir, Malay translation, English translation, and relationships among these entities. Therefore, concept maps instilled the element of learning through the conceptualization process and provided a platform for participants to resolve conflicting opinions and ambiguities of terms used immediately.
Similarity measurement is a critical component in any case-based reasoning (CBR) system. CBR is
a superior technique for solving new problems based on previous experiences. Main assumption in
CBR relies on the hypothesis that states similar problems should have similar solutions. This paper
describes a comparative analysis on several commonly used similarity measures (Canberra, Clark, and Normalized Euclidean distance) in retrieving phase of the case-based reasoning approach to facilitate supplier selection. In addition, the proposed agent-based supplier selection framework was designed to use customer’s defined weights to evaluate the price, volume, quality grade, and delivery date of supply materials, and also provide them with alternative products which are closest to their first order if it was out of stock. Finally, based on the proposed framework, a numerical example of the used approach is illustrated.