%0 Journal Article %1 HaOhEtAl14mtaa %A Ha, Inay %A Oh, Kyeong-Jin %A Hong, Myung-Duk %A Lee, Yeon-Ho %A Rosli, Ahmad Nurzid %A Jo, Geun-Sik %D 2014 %J Multimedia Tools and Applications %K v1205 springer paper ai semantic web information knowledge engineering processing ontology search zzz.th %N 2 %P 947-965 %R 10.1007/s11042-011-0889-8 %T Ontology-driven Visualization System for Semantic Searching %V 71 %X Technical manuals are very diverse, ranging from software to commodities, general instructions and technical manuals that deal with specific domains such as mechanical maintenance. Due to the vast amount of documentation, finding the information is a tedious and time consuming task, especially for the mechanics. It is also difficult to grasp relationships among contents in manuals. Many researchers have adopted ontology to solve these problems and semantically represent contents of manuals. However, if ontology becomes very large and complex, it is not easy to work with ontology. Visualization has been an effective way to grasp and manipulate ontology. In this research, we propose a new ontology model to represent and retrieve contents from the manuals. We have also designed a visualization system based on our proposed ontology. In order to model the ontology, we have analyzed aircraft maintenance process, extracted the concepts and defined relationships between concepts. After modeling ontology schema, all instances of ontology are created by instance creator. From here, raw data of maintenance manuals are preprocessed to well-formed format. Next, we create a set of rule mapping well-formed document and ontology schema. For the Component class, instance creator uses a classifier to separate all parts into Component and Primitive part class. If population task is complete, validity of data for created instances will be checked by JENA engine. The inference process will create inferred triples based on the ontology schema, and then the triples are saved into a triple repository. Our system then will use this triples repository to search necessary information and visualize the search results. We use the Prefuse toolkit to visualize the search results. With this, the mechanics can intuitively grasp the relationship between maintenance manuals using the provided information. This will allow the mechanics to easily obtain information for given tasks, reduce their time to search related information and understand the information through visualization.

@article{HaOhEtAl14mtaa, abstract = {Technical manuals are very diverse, ranging from software to commodities, general instructions and technical manuals that deal with specific domains such as mechanical maintenance. Due to the vast amount of documentation, finding the information is a tedious and time consuming task, especially for the mechanics. It is also difficult to grasp relationships among contents in manuals. Many researchers have adopted ontology to solve these problems and semantically represent contents of manuals. However, if ontology becomes very large and complex, it is not easy to work with ontology. Visualization has been an effective way to grasp and manipulate ontology. In this research, we propose a new ontology model to represent and retrieve contents from the manuals. We have also designed a visualization system based on our proposed ontology. In order to model the ontology, we have analyzed aircraft maintenance process, extracted the concepts and defined relationships between concepts. After modeling ontology schema, all instances of ontology are created by instance creator. From here, raw data of maintenance manuals are preprocessed to well-formed format. Next, we create a set of rule mapping well-formed document and ontology schema. For the Component class, instance creator uses a classifier to separate all parts into Component and Primitive part class. If population task is complete, validity of data for created instances will be checked by JENA engine. The inference process will create inferred triples based on the ontology schema, and then the triples are saved into a triple repository. Our system then will use this triples repository to search necessary information and visualize the search results. We use the Prefuse toolkit to visualize the search results. With this, the mechanics can intuitively grasp the relationship between maintenance manuals using the provided information. This will allow the mechanics to easily obtain information for given tasks, reduce their time to search related information and understand the information through visualization.}, added-at = {2014-09-20T17:25:46.000+0200}, author = {Ha, Inay and Oh, Kyeong-Jin and Hong, Myung-Duk and Lee, Yeon-Ho and Rosli, Ahmad Nurzid and Jo, Geun-Sik}, biburl = {https://www.bibsonomy.org/bibtex/2e9851a4433795effe0aeec5ea5c26886/flint63}, doi = {10.1007/s11042-011-0889-8}, file = {SpringerLink:2014/HaOhEtAl14mtaa.pdf:PDF}, groups = {public}, interhash = {209b179f00a268606dccb78e1e6eb90e}, intrahash = {e9851a4433795effe0aeec5ea5c26886}, issn = {1380-7501}, journal = {Multimedia Tools and Applications}, keywords = {v1205 springer paper ai semantic web information knowledge engineering processing ontology search zzz.th}, month = {#jul#}, number = 2, pages = {947-965}, timestamp = {2018-04-16T12:05:35.000+0200}, title = {Ontology-driven Visualization System for Semantic Searching}, username = {flint63}, volume = 71, year = 2014 }