Seheon Song

A goal-driven approach for adaptive service composition using planning

Abstract Due to the demands of complex services in our daily life, we must deal with various application devices in the dynamic and constantly changing ubiquitous computing environment with more adaptive and personalized application services. However, it becomes more difficult to realize users’ needs due to the ever increasing complexity of the task and the limitation of the capability of a single service alone. Creation of a new service on demand to carry out more complex tasks is possible through the composition of existing services. We have developed a preliminary prototype that supports dynamic service composition in a smart workspace environment. The system is able to achieve the desired user-tailored goals by composing the combination of available services in the smart office domain.

Music Ontology for Mood and Situation Reasoning to Support Music Retrieval and Recommendation

In this paper, we discuss the use of knowledge for analyzing and retrieving music contents semantically. First, we present Context-based Music Recommendation (COMUS) ontology to reason desired user emotion state from context and user preference information in the ontology. COMUS is a music dedicated ontology in OWL constructed by incorporating domain specific classes for music recommendation into the Music Ontology, which include situation, mood and musical features. More specifically, we describe the ontologies of mood and situation in music using low-level features like pitch or duration and musical factors like tempo or rhythm. Our proposed ontology defines generic as well as domain-specific concepts whose detection is important for the analysis and description of music in a specific domain. As a novelty, our ontology can express detailed and complicated relations among the music, moods and situations, enabling users to find appropriate music for the music retrieval and recommendation application. We present some of the experiments we performed as a case-study for music recommendation.

COMUS: Ontological and Rule-Based Reasoning for Music Recommendation System

In this paper, we propose Context-based Music Recommendation (COMUS) ontology for modeling users musical preferences and context for supporting reasoning about the users desired emotion and preferences. The COMUS provides an upper Music Ontology that captures concepts about the general properties of music such as title, artists and genre and also provides extensibility for adding domain-specific ontologies, such as Music Feature, Mood and Situation, in a hierarchical manner. The COMUS is music dedicated ontology in OWL constructed by incorporating domain specific classes for music recommendation into the Music Ontology. Using this context ontology, we believe that the use of logical reasoning rules by checking the consistency of context information, and reasoning over the high-level, implicit context from the low-level, explicit information. As a novelty, our ontology can express detailed and complicated relations among the music, moods and situations, enabling users to find appropriate music for the application. We present some of the experiments we performed as a case-study for music recommendation.

Implementing situation-aware and user-adaptive music recommendation service in semantic web and real-time multimedia computing environment

With the advent of the ubiquitous era, many studies have been devoted to various situation-aware services in the semantic web environment. One of the most challenging studies involves implementing a situation-aware personalized music recommendation service which considers the user’s situation and preferences. Situation-aware music recommendation requires multidisciplinary efforts including low-level feature extraction and analysis, music mood classification and human emotion prediction. In this paper, we propose a new scheme for a situation-aware/user-adaptive music recommendation service in the semantic web environment. To do this, we first discuss utilizing knowledge for analyzing and retrieving music contents semantically, and a user adaptive music recommendation scheme based on semantic web technologies that facilitates the development of domain knowledge and a rule set. Based on this discussion, we describe our Context-based Music Recommendation (COMUS) ontology for modeling the user’s musical preferences and contexts, and supporting reasoning about the user’s desired emotions and preferences. Basically, COMUS defines an upper music ontology that captures concepts on the general properties of music such as titles, artists and genres. In addition, it provides functionality for adding domain-specific ontologies, such as music features, moods and situations, in a hierarchical manner, for extensibility. Using this context ontology, we believe that logical reasoning rules can be inferred based on high-level (implicit) knowledge such as situations from low-level (explicit) knowledge. As an innovation, our ontology can express detailed and complicated relations among music clips, moods and situations, which enables users to find appropriate music. We present some of the experiments we performed as a case-study for music recommendation.

Ontology-based decision support for military information systems

In this paper, we propose an ontology-based decision support for military information services based on a multi-agent system. Our system consists of sensor agents to detect raw-level data, a context management agent for handling context data, an information service agent, an operational decision support agent, and user agents for maintaining user information. Our approach allows users in military domain to freely access to knowledge and to handle their own business by creating an environment of command and control system. It helps to reduce their workload and to simplify and share knowledge using our intelligent agent system.

Multiagent-Based Defensive Strategy System for Military Simulation

In ubiquitous computing, it needs to manage dynamic and various information from various sources and aware the situation. In the same way, it needs same capabilities including detecting and analyzing data from various sources, and recommending behaviors to a commander in a national defense domain. In this paper, we describe the adaptation of an open-source multi-agent architecture for a military defensive strategy system for battle simulation. We define the challenging problem of military defense. We take a community computing concept to adapt to handle dynamic environment, and the Cougaar framework to build our system which supports distributed multi-agent system.

A Plan-Based Service Composition for Work Process Agent in Ubiquitous Computing

In this paper, we discuss a Work Process Agent (WPA) that enables users to access a range of services for achieving their tasks with service composition based on planning in ubiquitous computing environment. WPA is a smart assistant application specializing in information service which needs to provide each users own user model and make the model be adapted to the users preferences dynamically. With WPA, users can achieve their task in a simple way. WPA employs a special BDI-based coordinator agent with planning for coordinating the individual WPA and external services. The plan-based service composition model works at abstraction level of process. This model makes it possible to reuse the frames of plans by making it independent from domain.

Mission-oriented service development using capability-based semantic recommendation for the internet of things

This paper presents a mission-oriented service development environment with web-based modeling tool that enable users create workflow-based service composition. This approach utilizes the ontology-based mission service model composed of mission, task, service and resource, and task/service recommendation. During developing the mission-oriented service, capability-based semantic matching and hierarchical relationship-based filtering are used for three types of recommendation. Also, we develop a modeling environment to monitor and execute the mission service application. In experiments, we have conducted on test beds in two domains such as military environment and smart building.

IoT Platform Implementation and Service Operating Method for Private Networks

ABSTRACT Today various IoT platforms exist, but most of them only consider IPv6, without other types of network including private network. They support, therefore, the private network to use virtual private network or through the hardware gateway. To solve this limitation, we propose a IoT platform that provides IoT Services on private networks. Also we verify this platform though constructing a testbed.Keywords:Internet of Things, Proxy, IoT Platform, Smart Building, Private Network 용이한 사설망 지원을 위한 IoT 플랫폼 구현 및 서비스 운영 방법 이 경 훈 † ⋅김 두 영 †† ⋅송 세 헌 ††† ⋅이 상 일 †††† ⋅박 재 현 †††† 요 약 현재 출시된 다양한 사물인터넷(IoT) 플랫폼은 대부분 IPv6의 네트워크 환경을 고려하여 개발되었지만, 아직까지 IPv4에서 IPv6로의 전환율은 저조하다. 따라서 IPv4기반의 네트워크에서 운용되는 IoT 플랫폼은 IP부족현상을 해결하기 위해 기구축된 사설망을 지원해야 한다. 기존 IoT 플랫폼들은 전문가에 의해 가상 사설망을 이용하거나 하드웨어 스위치/AP(Access Point)를 이용하여 사설망을 지원하고 있다. 본 연구에서는 기존 IoT 플랫폼들이 사설망 환경을 지원하기 위해 필요한 전문가 활용 또는 하드웨어 도입에 따른 추가 비용 문제를 해결하고, 비전문가도 사설망 환경에서 IoT 서비스를 제공할 수 있는 IoT 플랫폼을 개발하였다. 또한 IoT 플랫폼을 테스트베드에 적용하여 IoT 플랫폼의 기능 검증을 수행하였다.키워드:사물인터넷, 프록시, IoT 플랫폼, 스마트빌딩, 사설망

BDI Agent-Based Mobile Assistant Service on Android Using JAM

The study and development of agent-based system model are conducted continuously. Agent technology can be used to solve and enhance the complex and ubiquity system by making the intelligent system [1]. Specially, BDI agent model is suit to dynamic and open system. Recent few years, functions and role of mobile devices are extended and also deployment becomes easier. And beyond the limitation of physical properties, mobile environment becomes complex and dynamic by integrating of functions and constraints of resources. Accordingly, on mobile environment, the study of agent-based intelligent system and application is required. In this paper, BDI Agent-based Service is proposed for developing intelligent mobile application. We use JAM agent platform and environment is Android.