Marut Buranarach

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.

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.

Ontology Design Approaches for Development of an Excise Duty Recommender System

Excise duty is a type of tax charged on certain products and services. Determining an excise product class can be a difficult task since the regulation written in legal language can be difficult for the users to interpret. Excise duty recommender system aims to simplify the users’ effort in product classification task and reduce errors in tax payment. This paper describes an initiative to develop excise product ontology to provide explicit and formal definitions of excise products and their classifications. It focuses on ontology design approaches for some excise products to support excise duty recommender system development. Two excise products were used as case studies: beverage and petroleum products. Steps in defining product mapping rules and developing the recommender system are described. A Semantic Web-based system architecture was adopted to enable future support for data sharing and reuse based on the Linked Data technology.

A combined semantic social network analysis framework to integrate social media data

The technology of web 2.0 especially social networking has changed peoples behavior, attitudes, interactions, and relationships. User activities on social networking sites have created both explicit and implicit relationship. The relations can be distinguished for the sites with symmetric and asymmetric relationship types. In this paper, we propose a framework for semantic social network analysis for recommending user member groups on social media sites that combines explicit and implicit relationship. The framework utilizes semantic technology, i.e. ontology and RDF, to integrate the resulted data from different sites. Moreover, a presentation of a ontology design for user and activities referring to social network sites. An example of the integrated user profile is demonstrated using FOAF vocabulary.

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.

Ontology Based Orchid Knowledge Platform for Knowledge Services in Orchid Cluster

Orchid is one of the economic crops in world market. The varieties of shape, style, color and smell of orchids attract people to create products in many ways, such as cut orchid, orchid plant, bouquet, lei, corsage, and orchid loose bloom and so on. Thailand is one of the biggest exporters in orchid market. There are a lot of processes in the chain, such as reproduction, cultivation, market trend survey and analysis, transportation, international trade standard, traceability and so on. In order to provide a smart knowledge service, we have to 1) managing knowledge efficiently in terms of sharing and reusing knowledge and 2) providing knowledge which matches to stakeholders. In this paper, we propose a general framework on ontology base orchid cluster platform for developing a user-centric model of knowledge services in orchid cluster. We give some examples on semantic search model, recommended system model and tracking and monitoring model respectively.