JST Vol. 21 (1) Jan. 2013 - Pertanika Journal - Universiti Putra ...

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Che Mustapha Yusuf, J., Mohd Su’ud, M., Boursier, P. and Muhammad, A. designed system aims at providing users with data input, discovery and access to multiple media documents via rich ontology-based metadata describing them. The architecture comprehends the semantic matchmaking between user’s query and metadata of multi-format information using ontologies. This system architecture is called MIRIP (Multi-format Information Retrieval, Integration and Presentation), conformant to Service Oriented Architecture (SOA) standards (Sprott & Wilkes, 2011). A conceptual notion of the system is depicted in Fig.4. There are three sections involved in the overall process model, namely, provider, mediator and client sections. Details pertaining to the processing components in the architecture are as Fig.2. Provider section. This section comprises distributed data repositories, which are administered by different data owners. The data repository can be in the type of file-systems and special purpose databases (administration, GIS and multimedia). Information is stored as a set of files containing multiple media types such as GIS vector files, high-resolution aerial photographs and satellite images, snap photo images, audio-video clips and text documents. Metadata exist for managing the various media formats. To provide the semantic descriptions of each metadata, local (source) ontology is constructed according to bottom-up ontology principle. Concurrently, the local ontology is aligned with the upper-ontologies representing the common concepts and its relations. Mediator section. This section provides a searchable repository of data service descriptions, thus enabling data providers to publish their data and data requestors to search for these data. Semantic metadata-base permits the storage of metadata from various sources. Ontology component provides a common vocabulary to define the relationships between object classes once new metadata are (automatically) registered to the system. The ontology facilitates the retrieval system to identify the relevant media information through metadata, which are semantically annotated and matched to the terms specified in the query. Fig. 2: The MIRIP (Multi-format Information Retrieval, Integration and Presentation) architecture 220 Pertanika J. Sci. & Technol. 21 (1): 283 - 298 (2013)
Information Fusion via Integrated Metadata Using Hybrid Ontology Client section. This section enables human-machine interaction at registering data services, querying, navigating and accessing the information. By using the data registration interface (dRI), data providers can register their available metadata (push) to the catalogue service as data sources. The metadata catalogue is useful to facilitate data requestors to locate and evaluate the data services before it automatically makes a request to access the data. Once data services registration is made, service description is maintained by the mediator. The user query interface allows users to provide input to the query to automatically search the required information service. When the request method is posted, a user’s request will be sent to the mediator to search for matching values. If a data provider is found, the connection will be bonded between the data provider and the data requestor. The retrieval results and presentation interface allow search results from metadata catalogue to be presented in a ranked-list. These search results are delivered to the user through a combination of graphical and textual (e.g. descriptions) elements. Ontology Modelling for Semantic Integration In this work, ontology development takes advantages of the hybrid ontology with the implementation of top-down and bottom-up ontology designs (see Fig.4). The upper-ontology used in the hybrid ontology approach transfers the burden of information correlation and filters the query processing system (Mena et al., 2000). Following up the top-down design, the set of top-level ontology is firstly provided. Common terms are specified at a very abstract extent, so that a new source ontology can be easily mapped to the upper-ontology. If the new source contains a local concept that is not described in upper-ontology, the common concept that matches with the local concept will be established in the upper shared-vocabulary. Secondly, the source ontologies that contain more specific terms are extended from the primitive terms in the set of top-level ontology. Terms at both levels are comparable easily because the source ontologies only use the vocabulary of top-level ontology. Based on the bottom-up ontology design, the existing source schema and its instances are extracted to generate the source ontologies which contain more high level data descriptions. Then, the source ontologies of all disparate sources are mapped to the abstract concepts of top-level ontology which has been constructed earlier. In developing the ontology for the current environment and to enable bottom-up ontology mapping, each source must have at least one common concept. Some uncommon concepts that are considered important for query purpose will be declared as sharable in global ontology to avoid data loss. For instance, Source 1 holds concept ‘channels’ that describe the number of channels represented in the waveform data, such as 1 for mono or 2 for stereo. The concept, however, is not common to another source. Thus, the concept along with its possible subconcepts will be added in the shared vocabulary. The participating data sources in the integration process have no pre-existing ontologies. Thus, local ontology for each data source will be created with reference to shared-vocabulary. The body of the local ontology is extended to list more specific entities and properties. With no pre-existence of ontology, data sources still have the autonomy to maintain its own name concepts. The shared-ontologies (vocabularies) include top-level ontology to describe the primitive concepts and domain-specific disaster management ontology. At domain-specific level, Pertanika J. Sci. & Technol. 21 (1): 283 - 298 (2013) 221
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Journal of Science & Technology Jou
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International Advisory Board Adarsh
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Selected Articles from UPM-Malaysia
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ISSN: 0128-7680 © 2013 Universiti
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Aspect of Fatigue Analysis of Compo
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Application of Anthropometric Dimen
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Different Media Formulation on Bioc
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Heng, S. C., Ibrahim, Z. B., Suleim
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CONCLUSION Heng, S. C., Ibrahim, Z.
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Y. Yusuf, J. M. Juoi, Z. M. Rosli,
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Surface Roughness Y. Yusuf, J. M. J
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DISCUSSION Y. Yusuf, J. M. Juoi, Z.
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Modelling of Motion Resistance Rati
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The Empirical Method Modelling of M
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Assessment of Heavy Metal Pollution
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Physico-Chemical and Electrical Pro
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TABLE 1: (continued) Physico-Chemic
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Norhashila Hashim et al. effectiven
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Statistical Analysis Norhashila Has
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Norhashila Hashim et al. Post-hoc a
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Norhashila Hashim et al. Cubero, S.
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S. Ismail and K. A. Mohd Atan 4 4 p
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S. Ismail and K. A. Mohd Atan The f
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Lemma 1.1 The equation S. Ismail an
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CONCLUSION S. Ismail and K. A. Mohd
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INTRODUCTION Tajau, R. et al. A hig
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Aji, I. S., Zinudin, E. S., Khairul
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CONCLUSION Aji, I. S., Zinudin, E.
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D. Bachtiar, S. M. Sapuan, E. S. Za
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REFERENCES N. Maizatul, I. Norazowa
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CBIR Using Colour and Shape Fused F
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TABLE 5: Winners MRS The Role of Si
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REFEREES FOR THE PERTANIKA JOURNAL
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Guidelines for Authors Publication
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table should be prepared on a separ
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The Journal’s review process What
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Usability of Educational Computer G
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