Thepchai Supnithi

How Can We Form Effective Collaborative Learning Groups

Our research objectives include constructing a collaborative learning support system that detects appropriate situation for a learner to join in a collaborative learning session, and forms a collaborative learning group appropriate for the situation dynamically. In this paper, we describe a system of concepts concerning learning goals expected to attain by learners through collaborative learning process with justification by the learning theories. With the ontology, it will be possible to compare and synthesize the learning theories to design the collaborative learning settings.

Activity Recognition Using Context-Aware Infrastructure Ontology in Smart Home Domain

Nowadays, activity recognition has been proposed in several researches. It is attractive to improve the ability of the activity recognition system because existing research on activity recognition systems still have an error in an ambiguous cases. In this paper, we introduce the novel technique to improve the activity recognition system in smart home domain. We propose the three contributions in this research. Firstly, we design the context-aware infrastructure ontology for modelling the users context in the smart home. The innovative data, human posture, is added into the users context for reducing the ambiguous cases. Secondly, we propose the concepts to distinguish the activities by object-based and location-based concepts. We also present the description logic (DL) rules for making the human activity decision based on our proposed concepts. Lastly, We conduct the Ontology Based Activity Recognition (OBAR) system for two purposes: to recognize the human activity, and to search the semantic information in the system, called semantic ontology search (SOS) system. The results show the system can recognize the human activity correctly and also reduce the ambiguous case.

A Community-Driven Approach to Development of an Ontology-Based Application Management Framework

Although the semantic web standards are established, applications and uses of the data are relatively limited. This is partly due to high learning curve and efforts demanded in building semantic web and ontology-based applications. In this paper, we describe an ontology application management framework that aims to simplify creation and adoption of a semantic web application. The framework supports application development in ontology- database mapping, recommendation rule management and application templates focusing on semantic search and recommender system applications. We present some case studies that adopted our application framework in their projects. Evolution of the software tool significantly profited from the semantic web research community in Thailand who has contributed both in terms of the tool development and adoption support.

A Semantic Web Framework to Support Knowledge Management in Chronic Disease Healthcare

Improving quality of healthcare for people with chronic conditions requires informed and knowledgeable healthcare providers and patients. Decision support and clinical information system are two of the main components to support improving chronic care. In this paper, we describe an ongoing initiative that emphasizes the need for healthcare knowledge management to support both components. Ontology-based knowledge acquisition and modeling based on knowledge engineering approach provides an effective mechanism in capturing expert opinion in form of clinical practice guidelines. The Semantic Web framework is adopted in building a knowledge management platform that allows integration between the knowledge with patient databases and supported publications. We discuss one of the challenges, which is to apply the healthcare knowledge into existing healthcare provider environments by focusing on augmenting decision making and improving quality of patient care services.

OAM: An Ontology Application Management Framework for Simplifying Ontology-Based Semantic Web Application Development

Although the Semantic Web data standards are established, ontology-based applications built on the standards are relatively limited. This is partly due to high learning curve and efforts demanded in building ontology-based Semantic Web applications. In this paper, we describe an ontology application management (OAM) framework that aims to simplify creation and adoption of ontology-based application that is based on the Semantic Web technology. OAM introduces an intermediate layer between user application and programming and development environment in order to support ontology-based data publishing and access, abstraction and interoperability. The framework focuses on providing reusable and configurable data and application templates, which allow the users to create the applications without programming skill required. Three forms of templates are introduced: database to ontology mapping configuration, recommendation rule and application templates. We describe two case studies that adopted the framework: activity recognition in smart home domain and thalassemia clinical support system, and how the framework was used in simplifying development in both projects. In addition, we provide some performance evaluation results to show that, by limiting expressiveness of the rule language, a specialized form of recommendation processor can be developed for more efficient performance. Some advantages and limitations of the application framework in ontology-based applications are also discussed.

A review and comparison of rule languages and rule-based inference engines for the Semantic Web

With the Semantic Web data standards defined, more applications demand inference engines in providing support for intelligent processing of the Semantic Web data. Rule-based inference engines or rule-based reasoners are used in many domains such as supporting clinical decision support system, e-commerce recommender system, access control mechanism. In order to allow rule reuse and interoperation, several rule languages have been designed for the Web. In this paper, we review and compare some rule languages designed for the Web including FOL-RuleML, SWRL, Notation3, Jena rules and RIF. Some of the comparison criteria include rule expressiveness, syntax, production operations, and built-in functions. In addition, we review and compare some free and public domain rule-based reasoners including Jena inference engine, EYE, OWLIM-lite, BaseVISor and FuXi. Some of the comparison criteria include inference algorithms, supported programming languages, RDFS/OWL reasoning, rule languages and functions. The review and comparison results will provide some guideline for researchers and developers in choosing the rule languages and systems that match the application requirements.

A Syntactic Resource for Thai: CG Treebank

This paper presents Thai syntactic resource: Thai CG treebank, a categorial approach of language resources. Since there are very few Thai syntactic resources, we designed to create treebank based on CG formalism. Thai corpus was parsed with existing CG syntactic dictionary and LALR parser. The correct parsed trees were collected as preliminary CG treebank. It consists of 50,346 trees from 27,239 utterances. Trees can be split into three grammatical types. There are 12,876 sentential trees, 13,728 noun phrasal trees, and 18,342 verb phrasal trees. There are 17,847 utterances that obtain one tree, and an average tree per an utterance is 1.85.

RDF Dataset Management Framework for Data.go.th

Recently, Thailand has started initiating the Thailand open government data project that continuously triggers an increment in the number of open datasets. Open data is valuable when the data is reused, shared and integrated. Converting the existing datasets to the RDF format can increase the values of these datasets. In this paper, we present the architecture and processes for RDF dataset management for Data.go.th based on OAM Framework which supports the entire processes: RDF data publishing, and data querying. Our approach is different from other LOD platforms in that users do not require the knowledge of RDF and SPARQL. Our platform would facilitate data publishing and querying process for novice users and make it easier to use. This framework provides a common ontology-based search interface and RESTFul APIs constructed automatically for the datasets when they are published. With the provided services for the datasets, it can simplify the user’s tasks in publishing datasets and create applications for the datasets. In consuming the RDF data, we implemented a sample mash-up application which accessed the published weather and reservoir datasets from the Data.go.th website via RESTful APIs.

Location-Based Concept in Activity Log Ontology for Activity Recognition in Smart Home Domain

Activity recognition plays an important role in several researches. Nevertheless, the existing researches suffer various kinds of problems when human has a different lifestyle. To address these shortcomings, this paper proposes the activity log in the context-aware infrastructure ontology in order to interlink the history user’s context and current user’s context. In this approach, the location-based concept is built into the activity log for producing the description logic (DL) rules. The relationship between activities in the same location is investigated for making the result of activity recognition more accurately. We also conduct the semantic ontology search (SOS) system for evaluating the effectiveness of our proposed ideas. The semantic data can be retrieved through SOS system, including, human activity and activity of daily living (ADL). The results from SOS system showed the advantage overcome the existing system when uses the location-based concept in activity log ontology.

A development of knowledge representation for thalassemia prevention and control program

The spreading of thalassemia, the most common genetic disease in tropical areas, is increasing due to a migration thus the prevention and control program (PCP) of Thalassemia has been established. To better promote the yet unsuccessful PCP for thalassemia, ontology called PCPThalOnto is developed. The proposed ontology represents domain knowledge while a list of executable production rule is generated to represent operational knowledge. The PCPThalOnto consists of 1) class component to represent concepts of strategies, methodologies, techniques and activities of the PCP and 2) relation component to link between those classes or class and its instance. In the production rules, conditions for individual case determination are employed to execute a proper action. The well-constructed knowledge representation of PCP for thalassemia is developed as an electronic knowledge base for future applications to efficiently disseminate the underlying knowledge to people bridging the gap that deter the success of PCP.