Su-Cheng Haw

Short Communication: Ontology extraction from relational database: Concept hierarchy as background knowledge

Relational Database (RDB) has been widely used as the back-end database of information system. Contains a wealth of high-quality information, RDB provides conceptual model and metadata needed in the ontology construction. However, most of the existing ontology building approaches convert RDB schema without considering the knowledge resided in the database. This paper proposed the approach for ontology extraction on top of RDB by incorporating concept hierarchy as background knowledge. Incorporating the background knowledge in the building process of Web Ontology Language (OWL) ontology gives two main advantages: (1) accelerate the building process, thereby minimizing the conversion cost; (2) background knowledge guides the extraction of knowledge resided in database. The experimental simulation using a gold standard shows that the Taxonomic F-measure (TF) evaluation reaches 90% while Relation Overlap (RO) is 83.33%. In term of processing time, this approach is more efficient than the current approaches. In addition, our approach can be applied in any of the fields such as eGoverment, eCommerce and so on.

Data storage practices and query processing in XML databases: a survey

With the rapid emergence of XML as a data exchange standard over the Web, storing and querying XML data have become critical issues. The two main approaches to storing XML data are (1) to employ traditional storage such as relational database, object-oriented database and so on, and (2) to create an XML-specific native storage. The storage representation affects the efficiency of query processing. In this paper, firstly, we review the two approaches for storing XML data. Secondly, we review various query optimization techniques such as indexing, labeling and join algorithms to enhance query processing in both approaches. Next, we suggest an indexing classification scheme and discuss some of the current trends in indexing methods, which indicate a clear shift towards hybrid indexing.

Extending path summary and region encoding for efficient structural query processing in native XML databases

Optimizing query processing is always a challenging task in the XML database community. Current state-of-the-art approaches focus mainly on simple query. Yet, as the usage of XML shifts towards the data-oriented paradigm, more and more complex query processing needs to be supported. In this paper, we present TwigX-Guide, a hybrid system, which takes advantage of the beautiful features of path summary in DataGuide and region encoding in TwigStack to improve complex query processing. Experimental results indicate that TwigX-Guide can process complex queries on an average 38% better than the TwigStack algorithm, 31% better than TwigINLAB, 11% better than TwigStackList and about 9% better than TwigStackXB in terms of execution time.

s-XML: An efficient mapping scheme to bridge XML and relational database

XML has recently emerged as the leading medium for data storage and data transfer over the World Wide Web due to its adaptable structure and flexibility in defining the tags. Many organizations had adopted XML as the principal facet in their online business applications. On the other hand, relational database is still widely used as the back-end database in most organizations. The diversity of these models need to be taken into account to ensure transparent and seamless integration. In this paper, we propose s-XML, an effective mapping scheme to bridge XML and relational database. Experimental results indicate that (1) s-XML is robust in terms of database storage and data loading; (2) s-XML processes query efficiently for complex chain and twig queries; and (3) s-XML is able to support large and skew-structured dataset as compared to relational DTD, Attribute and Edge approaches.

Evolution of Structural Path Indexing Techniques in XML Databases: A Survey and Open Discussion

With the rapid emergence of XML as a data exchange and data transfer medium over the Web, querying XML data has become a major concern. Various optimization technologies, among them those based on XML, have been developed to solve query retrieval problems. In this paper, we suggest an indexing classification scheme and survey the existing path indexing techniques. We also analyze how each approach works, as well as its advantages and disadvantages. In addition, we discuss some of the current trends in indexing methods, which indicate a clear shift towards hybrid approaches. Hybrid systems open the possibility of balancing one technologys weakness with another technologys strengths.

Unsupervised abnormalities extraction and brain segmentation

In this paper, we propose a methodology consists of several unsupervised clustering techniques to acquire a satisfactory segmentation of computed tomography (CT) brain images. The ultimate goal of segmentation is to obtain three segmented images, which are the abnormalities, cerebrospinal fluid (CSF) and brain matter respectively. The proposed approach contains of two phase-segmentation methods. In the first phase segmentation, the combination of k-means and fuzzy c-means (FCM) methods is implemented to partition the images into the binary images. From the binary images, a decision tree is then utilized to annotate the connected component into normal and abnormal regions. For the second phase segmentation, the obtained experimental results have shown that modified FCM with population-diameter independent(PDI) segmentation is more feasible and yield satisfactory results.

Web Service Composition Using Windows Workflow for Cloud-Based Mobile Application

There is a lot of support provided by the mobile OS giants in cloud services. Besides providing their own services, they encourage developers to upload services into their cloud environment. However, when more services are being consumed in their cloud, more charges imposed to the users. Meanwhile, there exists a large amount of services which are available in public web service repositories. The cost of mobile development can be reduced by invoking and composing the services in sequence and upload or use them as a single service. We have used Windows Workflow for web service composition and the WSDL file produced can be hosted in our cloud environment and to be used by all. In this paper, we will be discussing on how to use Windows Workflow for web service composition for cloud-based mobile application. With the proposed system we will be able to save battery life time and increase the storage capacity.

Change Detection in Ontology Versioning: A Bottom-Up Approach by Incorporating Ontology Metadata Vocabulary

In ontology versioning, change detection should be related to dependent database or metadata, and vice-versa. Therefore, there is the need to detect change based on a bottom-up approach. This paper discusses bottom-up change detection by incorporating Ontology Metadata Vocabulary (OMV) as the interface to detect change from a database or metadata perspective. With respect to ontology versioning tasks, the approach emphasizes the use of change detection as an effort to preserve the compatibility serialization between ontology and knowledge-based systems (KBS). Our proposed framework and algorithm are presented.

ReLab: A subtree based labeling scheme for efficient XML query processing

XML has become the de facto standard in the real world application over the WWW. Thus, data or query processing is critical to ensure speed response time to cater user queries. Response time is often influenced by the complexity of labeling scheme which is not only used for unique identification of XML nodes, but for structural relationship purpose as well. The labeling scheme adopted is vital to ensure query processing is done flawlessly and promptly. In this paper, we introduce ReLab, a subtree based labeling scheme which generates labels using depth-first traversal. Our experimental evaluation indicated that ReLab outperformed Dietz and region numbering schemes in terms of time taken to generate labels for each XML nodes.

A survey on optimizing video and audio query retrieval in multimedia databases

With the advanced growth of the Internet, people are expecting systems to support variety of medias. This has therefore leads to new challenges such as the requirements to have new storage, retrieval and presentation of data. In addition, as the sizes continue to grow and the data become more and more complex, it is increasingly crucial and challenging to manage and analyze large amount of multimedia datasets effectively. In this paper, we suggest a query optimization classification scheme and survey the existing optimization techniques in multimedia databases. We also analyze how each approach works, the advantages and disadvantages of each approach focusing especially on video and audio data. The finding will reveal the best technique and serve as the guideline for young researchers.