Research is being made for users' convenient access to services such as personalized data and contents services. The use of information and the fusion of services in various devices and terminals suggest the necessity to know what personalization mechanism is used to provide high quality contents at a time and place desired by users. Existing mechanisms are not easy to be handled by other service providers because each service provider has different preference and personal information, and are very inconvenient because service users have to set up and manage by themselves. Thus, the present paper proposes a Semantic User Profiles Manager based on OSGi, middleware for the provision and extension of semantic services, in order to manage users' profiles dynamically regardless of service provider. In addition, this paper defines a personalized semantic profile that enables user profiling, ontological domain modeling and semantic reasoning. In order to test the validity of this paper, we implemented semantic profiles into a bundle running based on OSGi. When users enter the range of the service area and use various devices, the semantic service matches in correspondence with semantic user profiles. The proposed system can easily extend the matching of services to user profiles and matching between user profiles or between services.
As the amount of available information increases rapidly, sometimes the efficient search method alone is not enough to obtain necessary information in timely manner. Therefore additional support is needed to share the burden of searching for and filtering information. In the area of ubiquitous computing, computer systems existing everywhere should be able to proactively provide information just in time. Resource matching is essential in order to develop a system searching and recommending information required for a user in a specific context. This paper describes the infrastructure and methodology of information providing including systematical organization representation, ontological resource demarcation, and resource matching in the environment of a research institute. A specific application was developed to illustrate the proposed approach.
Kim, Sang-Kyun;Kim, Chul;Jang, Hyun-Chul;Yea, Sang-Jun;Song, Yea.Mi-Young
Journal of Information Management
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v.39
no.4
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pp.173-186
/
2008
We propose a mash-up system for searching herb, which can search the herbal information in oriental medicine fields using the various Open APIs. We in particular developed and opened two Open APIs which enable to search papers and projects in oriental medicine fields with the general Open APIs. These Open APIs can share and provide the expert knowledge in oriental medicine fields. The information for a herb in oriental medicine fields has various names and descriptions according to their sources unlike other fields. Thus, it is hard to get the results using one or two keywords such as the general search engines. To solve this problem, we in this paper propose a way to provide the more exact and extensive search results using the herb ontology with one hundred herbal information in oriental medicine fields.
Han, Young-Shin;Kim, Tae-Kyu;Jung, Jason J.;Jung, Chan-Ki;Lee, Chil-Gee
Journal of the Korea Society for Simulation
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v.18
no.1
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pp.27-34
/
2009
Currently network users, especially the number of internet users, increase rapidly. Also, high quality of service is required and this requirement results a sudden network traffic increment. As a result, an efficient management system for huge network traffic becomes an important issue. Ontology/data engineering based context awareness using the System Entity Structure (SES) concepts enables network administrators to access traffic data easily and efficiently. The network traffic analysis system, which is studied in this paper, is designed and implemented based on a model and simulation using data engineering methodology to be avaiable in evaluating large network traffic data. Extensible Markup Language (XML) is used for metadata language in this system. The information which is extracted from the network traffic analysis system could be modeled and simulated in Discrete Event Simulation (DEVS) methodology for further works such as post simulation evaluation, web services, and etc.
As defense science and technology are developing, smart weapons are being developed continually. The collection and analysis of the future strategic weapon information from all over the world have become a greater priority because information sharing became active. So, a system to manage and analyze heterogeneous defense intelligence is required. Semantic Web is the next generation knowledge information management technology for integrating, searching and navigating heterogeneous knowledge resource. Recently, Semantic Web is wildly being used in intelligent information management system. Semantic Web supports the analysis with the high reliability because it supports the simple keyword search as well as the semantic based information retrieval. In this paper, we propose the semantic web based multi-dimensional information analysis system on the national defense weapons that constructs ontology for various weapons information such as weapon specifications, nations, manufacturers and technologies and searches and analyses the specific weapon based on ontology. The proposed system supports the semantic search and multi-dimensional information analysis based on the relations between weapon specifications. Also, our system improves the efficiency on acquiring smart weapon information because it is developed with ontology based on military experts' knowledge and various web documents related with various weapons and intelligent search service.
In this paper, we implement an automated composition system of web services using hybrid techniques that merge the benefit of BPEL techniques, with the advantage of OWL-S, BPEL techniques have practical capabilities that fulfil the needs of the business environment such as fault handling and transaction management. However, the main shortcoming of these techniques is the static composition approach, where the service selection and flow management are done a priori and manually. In contrast, OWL-S techniques use ontologies to provide a mechanism to describe the web services functionality in machine-understandable form, making it possible to discover, and integrate web services automatically. This allows for the dynamic integration of compatible web services, possibly discovered at run time, into the composition schema. However, the development of these approaches is still in its infancy and has been largely detached from the BPEL composition effort. In this work, we describe the design of the SemanticBPEL architecture that is a hybrid system of BPEL4WS and OWL-S, and propose algorithms for web service search and integration. In particular, the SemanticBPEL has been implemented based on the open source tools. The proposed system is compared with existing BPEL systems by functional analysis. These comparisions show that our system outperforms existing systems.
Knowledge map is widely used to represent knowledge in many domains. This paper presents a method of integrating the national R&D data and assists of users to navigate the integrated data via using a knowledge map service. The knowledge map service is built by using a lightweight ontology and a topic modeling method. The national R&D data is integrated with the research project as its center, i.e., the other R&D data such as research papers, patents, and reports are connected with the research project as its outputs. The lightweight ontology is used to represent the simple relationships between the integrated data such as project-outputs relationships, document-author relationships, and document-topic relationships. Knowledge map enables us to infer further relationships such as co-author and co-topic relationships. To extract the relationships between the integrated data, a Relational Data-to-Triples transformer is implemented. Also, a topic modeling approach is introduced to extract the document-topic relationships. A triple store is used to manage and process the ontology data while preserving the network characteristics of knowledge map service. Knowledge map can be divided into two types: one is a knowledge map used in the area of knowledge management to store, manage and process the organizations' data as knowledge, the other is a knowledge map for analyzing and representing knowledge extracted from the science & technology documents. This research focuses on the latter one. In this research, a knowledge map service is introduced for integrating the national R&D data obtained from National Digital Science Library (NDSL) and National Science & Technology Information Service (NTIS), which are two major repository and service of national R&D data servicing in Korea. A lightweight ontology is used to design and build a knowledge map. Using the lightweight ontology enables us to represent and process knowledge as a simple network and it fits in with the knowledge navigation and visualization characteristics of the knowledge map. The lightweight ontology is used to represent the entities and their relationships in the knowledge maps, and an ontology repository is created to store and process the ontology. In the ontologies, researchers are implicitly connected by the national R&D data as the author relationships and the performer relationships. A knowledge map for displaying researchers' network is created, and the researchers' network is created by the co-authoring relationships of the national R&D documents and the co-participation relationships of the national R&D projects. To sum up, a knowledge map-service system based on topic modeling and ontology is introduced for processing knowledge about the national R&D data such as research projects, papers, patent, project reports, and Global Trends Briefing (GTB) data. The system has goals 1) to integrate the national R&D data obtained from NDSL and NTIS, 2) to provide a semantic & topic based information search on the integrated data, and 3) to provide a knowledge map services based on the semantic analysis and knowledge processing. The S&T information such as research papers, research reports, patents and GTB are daily updated from NDSL, and the R&D projects information including their participants and output information are updated from the NTIS. The S&T information and the national R&D information are obtained and integrated to the integrated database. Knowledge base is constructed by transforming the relational data into triples referencing R&D ontology. In addition, a topic modeling method is employed to extract the relationships between the S&T documents and topic keyword/s representing the documents. The topic modeling approach enables us to extract the relationships and topic keyword/s based on the semantics, not based on the simple keyword/s. Lastly, we show an experiment on the construction of the integrated knowledge base using the lightweight ontology and topic modeling, and the knowledge map services created based on the knowledge base are also introduced.
Journal of the Korean Society for information Management
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v.30
no.3
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pp.297-315
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2013
Anyone curious to easily access and learn Korean history has become interested in Korean history data bases, which will provide accurate and reliable historical information. Furthermore, user demands for information sharing and reusability, available through setting up a semantic web, have been increased, which have taken the shape of linked data. Efforts have been made to construct public data bases containing readily usable contents a user can understand and utilize with ease. They have been produced by several organizations, portal sites, and individuals, trying to deviate from existing mainstreams - expert-based text data bases. A problem with those data bases is that they have not considered such vital factors as the sharing and utilizing of information as a whole. This study suggests a LOD-based Korean history contents implementation system, providing rich information environment by way of multi-dimensional web-data connections. In doing so, this system has tried a historic information circulation service system which is based on information sharing and connecting.
Recently, the rapid progress of a number of standardized web technologies and the proliferation of web users in the world bring an explosive increase of producing and consuming information documents on the web. In addition, most companies have produced, shared, and managed a huge number of information documents that are needed to perform their businesses. They also have discretionally raked, stored and managed a number of web documents published on the web for their business. Along with this increase of information documents that should be managed in the companies, the need of a solution to locate information documents more accurately among a huge number of information sources have increased. In order to satisfy the need of accurate search, the market size of search engine solution market is becoming increasingly expended. The most important functionality among much functionality provided by search engine is to locate accurate information documents from a huge information sources. The major metric to evaluate the accuracy of search engine is relevance that consists of two measures, precision and recall. Precision is thought of as a measure of exactness, that is, what percentage of information considered as true answer are actually such, whereas recall is a measure of completeness, that is, what percentage of true answer are retrieved as such. These two measures can be used differently according to the applied domain. If we need to exhaustively search information such as patent documents and research papers, it is better to increase the recall. On the other hand, when the amount of information is small scale, it is better to increase precision. Most of existing web search engines typically uses a keyword search method that returns web documents including keywords which correspond to search words entered by a user. This method has a virtue of locating all web documents quickly, even though many search words are inputted. However, this method has a fundamental imitation of not considering search intention of a user, thereby retrieving irrelevant results as well as relevant ones. Thus, it takes additional time and effort to set relevant ones out from all results returned by a search engine. That is, keyword search method can increase recall, while it is difficult to locate web documents which a user actually want to find because it does not provide a means of understanding the intention of a user and reflecting it to a progress of searching information. Thus, this research suggests a new method of combining ontology-based search solution with core search functionalities provided by existing search engine solutions. The method enables a search engine to provide optimal search results by inferenceing the search intention of a user. To that end, we build an ontology which contains concepts and relationships among them in a specific domain. The ontology is used to inference synonyms of a set of search keywords inputted by a user, thereby making the search intention of the user reflected into the progress of searching information more actively compared to existing search engines. Based on the proposed method we implement a prototype search system and test the system in the patent domain where we experiment on searching relevant documents associated with a patent. The experiment shows that our system increases the both recall and precision in accuracy and augments the search productivity by using improved user interface that enables a user to interact with our search system effectively. In the future research, we will study a means of validating the better performance of our prototype system by comparing other search engine solution and will extend the applied domain into other domains for searching information such as portal.
Kim Jongnam;Jung Junwon;Min Kyeung-Sub;Kim Hyoung-Joo
Journal of KIISE:Databases
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v.32
no.5
/
pp.526-535
/
2005
Ontology is a methodology on describing specific concepts and their relationships, and it is being considered important more and more as semantic web and variety of knowledge management systems are being highlighted. Ontology uses the relationships among concerts to represent some concrete semantics of specific concept. When we want to get some useful information from ontology, we severely have to process the transitive relationships because most of relationships among concepts represent transitivity. Technically, it causes recursive calls to process such transitive closure queries with heavy costs. This paper describes the efficient technique for processing transitive closure queries in ontology. To the purpose of it, we examine some approaches of current systems for transitive closure queries, and propose a technique by graph labeling scheme. Basically, we assume large size of ontology, and then we show that our approach gives relative efficiency in processing of transitive closure, queries.
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