• Title/Summary/Keyword: Semantic search

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Quality Dimensions Affecting the Effectiveness of a Semantic-Web Search Engine (검색 효과성에 영향을 미치는 시맨틱웹 검색시스템 품질요인에 관한 연구)

  • Han, Dong-Il;Hong, Il-Yoo
    • Asia pacific journal of information systems
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    • v.19 no.1
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    • pp.1-31
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    • 2009
  • This paper empirically examines factors that potentially influence the success of a Web-based semantic search engine. A research model has been proposed that shows the impact of quality-related factors upon the effectiveness of a semantic search engine, based on DeLone and McLean's(2003) information systems success model. An empirical study has been conducted to test hypotheses formulated around the research model, and statistical methods were applied to analyze gathered data and draw conclusions. Implications for academics and practitioners are offered based on the findings of the study. The proposed model includes three quality dimensions of a Web-based semantic search engine-namely, information quality, system quality and service quality. These three dimensions each have measures designed to collectively assess the respective dimension. The model is intended to examine the relationship between measures of these quality dimensions and measures of two dependent constructs, including individuals' net benefit and user satisfaction. Individuals' net benefit was measured by the extent to which the user's information needs were adequately met, whereas user satisfaction was measured by a combination of the perceived satisfaction with search results and the perceived satisfaction with the overall system. A total of 23 hypotheses have been formulated around the model, and a questionnaire survey has been conducted using a functional semantic search website created by KT and Hakia, so as to collect data to validate the model. Copies of a questionnaire form were handed out in person to 160 research associates and employees working in the area of designing and developing semantic search engines. Those who received the form, 148 respondents returned valid responses. The survey form asked respondents to use the given website to answer questions concerning the system. The results of the empirical study have indicated that, of the three quality dimensions, information quality was found to have the strongest association with the effectiveness of a Web-based semantic search engine. This finding is consistent with the observation in the literature that the aspects of the information quality should serve as a basis for evaluating the search outcomes from a semantic search engine. Measures under the information quality dimension that have a positive effect on informational gratification and user satisfaction were found to be recall and currency. Under the system quality dimension, response time and interactivity, were positively related to informational gratification. On the other hand, only one measure under the service quality dimension, reliability was found to have a positive relationship with user satisfaction. The results were based on the seven hypotheses that have been accepted. One may wonder why 15 out of the 23 hypotheses have been rejected and question the theoretical soundness of the model. However, the correlations between independent variables and dependent variables came out to be fairly high. This suggests that the structural equation model yielded results inconsistent with those of coefficient analysis, because the structural equation model intends to examine the relationship among independent variables as well as the relationship between independent variables and dependent variables. The findings offer some useful implications for owners of a semantic search engine, as far as the design and maintenance of the website is concerned. First, the system should be designed to respond to the user's query as fast as possible. Also it should be designed to support the search process by recommending, revising, and choosing a search query, so as to maximize users' interactions with the system. Second, the system should present search results with maximum recall and currency to effectively meet the users' expectations. Third, it should be capable of providing online services in a reliable and trustworthy manner. Finally, effective increase in user satisfaction requires the improvement of quality factors associated with a semantic search engine, which would in turn help increase the informational gratification for users. The proposed model can serve as a useful framework for measuring the success of a Web-based semantic search engine. Applying the search engine success framework to the measurement of search engine effectiveness has the potential to provide an outline of what areas of a semantic search engine needs improvement, in order to better meet information needs of users. Further research will be needed to make this idea a reality.

A Semantic Service Discovery Network for Large-Scale Ubiquitous Computing Environments

  • Kang, Sae-Hoon;Kim, Dae-Woong;Lee, Young-Hee;Hyun, Soon-J.;Lee, Dong-Man;Lee, Ben
    • ETRI Journal
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    • v.29 no.5
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    • pp.545-558
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    • 2007
  • This paper presents an efficient semantic service discovery scheme called UbiSearch for a large-scale ubiquitous computing environment. A semantic service discovery network in the semantic vector space is proposed where services that are semantically close to each other are mapped to nearby positions so that the similar services are registered in a cluster of resolvers. Using this mapping technique, the search space for a query is efficiently confined within a minimized cluster region while maintaining high accuracy in comparison to the centralized scheme. The proposed semantic service discovery network provides a number of novel features to evenly distribute service indexes to the resolvers and reduce the number of resolvers to visit. Our simulation study shows that UbiSearch provides good semantic searchability as compared to the centralized indexing system. At the same time, it supports scalable semantic queries with low communication overhead, balanced load distribution among resolvers for service registration and query processing, and personalized semantic matching.

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Video Data Modeling for Supporting Structural and Semantic Retrieval (구조 및 의미 검색을 지원하는 비디오 데이타의 모델링)

  • 복경수;유재수;조기형
    • Journal of KIISE:Databases
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    • v.30 no.3
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    • pp.237-251
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    • 2003
  • In this paper, we propose a video retrieval system to search logical structure and semantic contents of video data efficiently. The proposed system employs a layered modelling method that orBanifes video data in raw data layer, content layer and key frame layer. The layered modelling of the proposed system represents logical structures and semantic contents of video data in content layer. Also, the proposed system supports various types of searches such as text search, visual feature based similarity search, spatio-temporal relationship based similarity search and semantic contents search.

An Associative Search System for Mobile Life-log Semantic Networks based on Visualization (시각화 기반 모바일 라이프 로그 시맨틱 네트워크 연관 검색 시스템)

  • Oh, Keun-Hyun;Kim, Yong-Jun;Cho, Sung-Bae
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.6
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    • pp.727-731
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    • 2010
  • Recently, mobile life-log data are collected by mobile devices and used to recode one's life. In order to help a user search data, a mobile life-log semantic network is introduced for storing logs and retrieving associative information. However, associative search systems on common semantic networks in previous studies provide for a user with only found data as text to users. This paper proposes an associative search system for mobile life-log semantic network that supports selection and keyword associative search of which a process and result are a visualized graph representing associative data and their relationships when a user inputs a keyword for search. In addition, by using semantic abstraction, the system improves user's understanding of search result and simplifies the resulting graph. The system's usability was tested by an experiment comparing the system and a text-based search system.

A Method for build an Ontology-based Component Semantic Search System for Reconfiguration of Weapon System (무기체계 재구성을 위한 온톨로지 기반 컴포넌트 시맨틱 검색 시스템 구축 방법)

  • Seo, Dong Jin;Seo, Yoonho
    • Journal of the Korea Society for Simulation
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    • v.25 no.1
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    • pp.11-20
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    • 2016
  • Recently in the field of defense Modeling and Simulation (M&S), Component-Based Development technology is widely applying to save the cost and increase the reusability of weapon system development. Related with this, researches for rapid reconfiguration and simulation of the component-standardized weapon system is actively carrying out. To rapidly reconfigure the new weapon system, complex and various functions of component information has to be effectively searched. So, it requires differentiated search technique unlike existing Keyword-based Search method. Semantic Search System provides semantically related information among the extensive information. In this research, metadata of weapon system components and their representative functional words are built as an ontology. And it provides an ontology-based semantic search system.

Semantic Search : A Survey (시맨틱 검색 : 서베이)

  • Park, Jin-Soo;Kim, Nam-Won;Choi, Min-Jung;Jin, Zhe;Choi, Young-Seok
    • Journal of Intelligence and Information Systems
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    • v.17 no.4
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    • pp.19-36
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    • 2011
  • Since the ambitious declaration of the vision of the Semantic Web, a growing number of studies on semantic search have recently been made. However, we recognize that our community has not so much accomplished despite those efforts. We analyze two underlying problems : a lack of a shared notion of semantic search that guides current research, and a lack of a comprehensive view that envisions future work. Based on this diagnosis, we start by defining semantic search as the process of retrieving desired information in response to user's input using semantic technologies such as ontologies. Then, we propose a classification framework in order for the community to obtain the better understanding of semantic search. The proposed classification framework consists of input processing, target source, search methodology, results ranking, and output data type. Last, we apply our proposed framework to prior studies and suggest future research directions.

A Mobile Semantic Integrated Search System of National Defense Research Information (국방연구정보의 모바일 시맨틱 통합검색 시스템)

  • Yoo, Dong-Hee;Ra, Min-Young
    • The KIPS Transactions:PartB
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    • v.18B no.5
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    • pp.295-304
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    • 2011
  • To effectively manage research information in the field of national defense, metadata about the information should be managed systematically, and an integrated system to help convergence and management of the information should be implemented based on the metadata. In addition, the system should provide the users with effective integrated search services in a mobile environment, because searching via the use of mobile devices is increasing. The objective of this paper is to suggest a MSISS (Mobile Semantic Integrated Search System), which satisfies the requirements for effective management of the national defense research information. Specifically, we defined national defense research ontologies and national defense research rules after analyzing the Dublin Core metadata and database information of the major military research institutions. We implemented a prototype system for MSISS to demonstrate the use of the ontologies and rules for semantic integrated searching of the military research information. We also presented a triple-based search service to support semantic integrated search in a mobile environment and suggested future mobile semantic integrated search services.

A Keyword Query Processing Technique of OWL Data using Semantic Relationships (의미적 관계를 이용한 OWL 데이터의 키워드 질의 처리 기법)

  • Kim, Youn Hee;Kim, Sung Wan
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.9 no.1
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    • pp.59-72
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    • 2013
  • In this paper, we propose a keyword query processing technique based on semantic relationships for OWL data. The proposed keyword query processing technique can improve user's search satisfaction by performing two types of associative search. The first associative search uses information inferred by the relationships between classes or properties during keyword query processing. And it supports to search all information resources that are either directly or indirectly related with query keywords by semantic relationships between information resources. The second associative search returns not only information resources related with query keywords but also values of properties of them. We design a storage schema and index structures to support the proposed technique. And we propose evaluation functions to rank retrieved information resources according to three criteria. Finally, we evaluate the validity and accuracy of the proposed technique through experiments. The proposed technique can be utilized in a variety of fields, such as paper retrieval and multimedia retrieval.

Ontology Knowledge Base Scheme for User Query Semantic Interpretation (사용자 질의 의미 해석을 위한 온톨로지 지식베이스 스키마 구축)

  • Doh, Hana;Lee, Moo-Hun;Jeong, Hoon;Choi, Eui-In
    • Journal of Digital Convergence
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    • v.11 no.3
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    • pp.285-292
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    • 2013
  • The method of recent information retrieval passes into an semantic search to provide more accurate results than keyword-based search. But in common user case, they are still accustomed to using existing keyword-based search. Hence they are hard to create a typed structured query language. In this paper, we propose to ontology knowledge-base scheme for query interpretation of these user. The proposed scheme was designed based on the OWL-DL for description logic reasoning, it can provide a richer representation of the relationship between the object by using SWRL(Semantic Web Rule Language). Finally, we are describe the experimental results of the similarity measurement for verification of a user query semantic interpretation.

Query Expansion System for Semantic Contents Retrieval (시맨틱 콘텐츠 검색을 위한 질의 확장 시스템)

  • Lee, Moo-Hun;Choi, Eui-In
    • Journal of Digital Convergence
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    • v.10 no.10
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    • pp.307-312
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    • 2012
  • For semantic search methods to provide more accurate results than keyword-based search in a logical representation that uses a knowledge base are being studied. Than most of the user to use formal query language and schema used to interpret the meaning of a user keyword. In this paper, we propose to expand the user query for semantic search. In the proposed system, user query expansion component and a component to adjust the results to interpret user queries to take advantage of the knowledge base associated with a search term. Finally, a user query semantic interpretation, the proposed scheme to verify the experimental results of the prototype system is described.