• Title/Summary/Keyword: Semantic query

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Semantic schema data processing using cache mechanism (캐쉬메카니즘을 이용한 시맨틱 스키마 데이터 처리)

  • Kim, Byung-Gon;Oh, Sung-Kyun
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.3
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    • pp.89-97
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    • 2011
  • In semantic web information system like ontology that access distributed information from network, efficient query processing requires an advanced caching mechanism to reduce the query response time. P2P network system have become an important infra structure in web environment. In P2P network system, when the query is initiated, reducing the demand of data transformation to source peer is important aspect of efficient query processing. Caching of query and query result takes a particular advantage by adding or removing a query term. Many of the answers may already be cached and can be delivered to the user right away. In web environment, semantic caching method has been proposed which manages the cache as a collection of semantic regions. In this paper, we propose the semantic caching technique in cluster environment of peers. Especially, using schema data filtering technique and schema similarity cache replacement method, we enhanced the query processing efficiency.

Relational Database Structure for Preserving Multi-role Topics in Topic Map (토픽맵의 다중역할 토픽 보존을 위한 관계형 데이터베이스 구조)

  • Jung, Yoonsoo;Y., Choon;Kim, Namgyu
    • The Journal of Information Systems
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    • v.18 no.3
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    • pp.327-349
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    • 2009
  • Traditional keyword-based searching methods suffer from low accuracy and high complexity due to the rapid growth in the amount of information. Accordingly, many researchers attempt to implement a so-called semantic search which is based on the semantics of the user's query. Semantic information can be described using a semantic modeling language, such as Topic Map. In this paper, we propose a new method to map a topic map to a traditional Relational Database (RDB) without any information loss. Although there have been a few attempts to map topic maps to RDB, they have paid scant attention to handling multi-role topics. In this paper, we propose a new storage structure to map multi-role topics to traditional RDB. The proposed structure consists of a mapping table, role tables, and content tables. Additionally, we devise a query translator to convert a user's query to one appropriate to the proposed structure.

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Preference-based search technology for the user query semantic interpretation (사용자 질의 의미 해석을 위한 선호도 기반 검색 기술)

  • Jeong, Hoon;Lee, Moo-Hun;Do, Hana;Choi, Eui-In
    • Journal of Digital Convergence
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    • v.11 no.2
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    • pp.271-277
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    • 2013
  • Typical semantic search query for Semantic search promises to provide more accurate result than present-day keyword matching-based search by using the knowledge base represented logically. Existing keyword-based retrieval system is Preference for the semantic interpretation of a user's query is not the meaning of the user keywords of interconnect, you can not search. In this paper, we propose a method that can provide accurate results to meet the user's search intent to user preference based evaluation by ranking search. The proposed scheme is Integrated ontology-based knowledge base built on the formal structure of the semantic interpretation process based on ontology knowledge base system.

Semantic Conceptual Relational Similarity Based Web Document Clustering for Efficient Information Retrieval Using Semantic Ontology

  • Selvalakshmi, B;Subramaniam, M;Sathiyasekar, K
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.9
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    • pp.3102-3119
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    • 2021
  • In the modern rapid growing web era, the scope of web publication is about accessing the web resources. Due to the increased size of web, the search engines face many challenges, in indexing the web pages as well as producing result to the user query. Methodologies discussed in literatures towards clustering web documents suffer in producing higher clustering accuracy. Problem is mitigated using, the proposed scheme, Semantic Conceptual Relational Similarity (SCRS) based clustering algorithm which, considers the relationship of any document in two ways, to measure the similarity. One is with the number of semantic relations of any document class covered by the input document and the second is the number of conceptual relation the input document covers towards any document class. With a given data set Ds, the method estimates the SCRS measure for each document Di towards available class of documents. As a result, a class with maximum SCRS is identified and the document is indexed on the selected class. The SCRS measure is measured according to the semantic relevancy of input document towards each document of any class. Similarly, the input query has been measured for Query Relational Semantic Score (QRSS) towards each class of documents. Based on the value of QRSS measure, the document class is identified, retrieved and ranked based on the QRSS measure to produce final population. In both the way, the semantic measures are estimated based on the concepts available in semantic ontology. The proposed method had risen efficient result in indexing as well as search efficiency also has been improved.

Query Rewriting and Indexing Schemes for Distributed Systems based on the Semantic Web (시맨틱 웹 기반의 분산 시스템을 위한 질의 변환 및 인덱싱 기법)

  • Chae, Kwang-Ju;Kim, Youn-Hee;Lim, Hae-Chull
    • Journal of KIISE:Computing Practices and Letters
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    • v.14 no.7
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    • pp.718-722
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    • 2008
  • Ontology plays an important role of the Semantic Web to describe meaning and reasoning of resources. Ontology has more rich expressive power through OWL that is a next standard representation language recommended by W3C. As the Semantic Web is widely known, an amount of information resources on the Web is growing rapidly and the related information resources are placed in distributed systems on the Web. So, for providing seamless services without the awareness of far distance, efficient management of the distributed information resources is required. Especially, sear ching fast for local repositories that include data related to user's queries is important to the performance of systems in the distributed environment. In this paper, first, we propose an index structure to search local repositories related to queries in the distributed Semantic Web. Second, we propose a query rewriting strategy to extend given user's query using various expression of OWL. Through the proposed index and query strategy, we can utilize various expressions of OWL and find local repositories related to all query patterns on the Semantic Web.

A Natural Language Query Framework for the Semantic Web

  • Kim, Jin-Sung
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.1
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    • pp.127-132
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    • 2008
  • This study proposes a Natural Language Query Framework (NLQF) for the semantic web. It supports an intelligent inference at a semantic level. Most of previous researches focused on the knowledge representation on the semantic web. However, to revitalize the intelligent e-business on the semantic web, there is a need for semantic level inference to the web information. To satisfy the need, we will review the knowledge/resource representation on the semantic web such as RDF, Ontology and Conceptual Graph (CG), and then discuss about the natural language (NL) inference. The result of this research could support a natural interface for the semantic web. Furthermore, we expect that the NLQF can be used in the semantic web-based business communications.

A Semantic-based Video Retrieval System using Method of Automatic Annotation Update and Multi-Partition Color Histogram (자동 주석 갱신 및 멀티 분할 색상 히스토그램 기법을 이용한 의미기반 비디오 검색 시스템)

  • 이광형;전문석
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.8C
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    • pp.1133-1141
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    • 2004
  • In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic-based retrieval method can be available for various query of users. In this paper, we propose semantic-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. From experiment, the designed and implemented system showed high precision ratio in performance assessment more than 90 percents.

Design of Relational Storage Schema and Query Processing for Semantic Web Documents (시맨틱 웹 문서를 위한 관계형 저장 스키마 설계 및 질의 처리 기법)

  • Lee, Soon-Mi
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.1
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    • pp.35-45
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    • 2009
  • According to the widespread use of ontology documents, a management system which store ontology data and process queries is needed for retrieving semantic information efficiently. In this paper I propose a storage schema that stores and retrieves semantic web documents based on RDF/RDFS ontology language developed by W3C in a relational databases. Specially, the proposed storage schema is designed to retrieve efficiently hierarchy information and to increase efficiency of query processing. Also, I describe a mechanism to transform RQL semantic queries to SQL relational queries and build up database using MS-ACCESS and implement in this paper. According to the result of implementation, we can blow that not only data query based on triple model but also query for schema and hierarchy information are transformed simply to SQL.

Natural Language Query Framework on the Semantic Web

  • Kim, Jin-Sung
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.04a
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    • pp.189-192
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    • 2007
  • This study proposes a Natural Language Query Framework (NLQF) on the semantic web to support the intelligent deduction at semantic level. A large number of former researches are focused on the knowledge representation on the semantic web. However, to revitalize the intelligent agent (IA)-based automated e-business contract with human customers, there is a need for semantic level approach to the web information. To enable accessing web information at semantic level, this paper discusses the pattern of complex natural language processing at first, and then the semantic web-based natural language inference in e-business environment. The NL-based approach could help the IAs on the web to communicate with customers and other IAs with more natural interface than traditional HTML-based web information. Therefore, our proposed NLQF will be used in semantic web-based intelligent e-business contracts between customers and IAs.

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Query-based Document Summarization using Pseudo Relevance Feedback based on Semantic Features and WordNet (의미특징과 워드넷 기반의 의사 연관 피드백을 사용한 질의기반 문서요약)

  • Kim, Chul-Won;Park, Sun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.7
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    • pp.1517-1524
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    • 2011
  • In this paper, a new document summarization method, which uses the semantic features and the pseudo relevance feedback (PRF) by using WordNet, is introduced to extract meaningful sentences relevant to a user query. The proposed method can improve the quality of document summaries because the inherent semantic of the documents are well reflected by the semantic feature from NMF. In addition, it uses the PRF by the semantic features and WordNet to reduce the semantic gap between the high level user's requirement and the low level vector representation. The experimental results demonstrate that the proposed method achieves better performance that the other methods.