• Title/Summary/Keyword: Fuzzy Query

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Effectual Fuzzy Query Evaluation Method based on Fuzzy Linguistic Matrix in Information Retrieval (정보검색에서 퍼지 언어 매트릭스에 근거한 효율적인 퍼지 질의 평가 방법)

  • 최명복;김민구
    • Journal of the Korean Institute of Intelligent Systems
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    • v.10 no.3
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    • pp.218-227
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    • 2000
  • In this paper, we present a new fuzzy information retrieval method based on thesaurus. In the proposed method th thesaurus is represented by a fuzzy linguistic matrix, where the elements in fuzzy linguistic matrix represent a qualitative linguistic values between terms. In the fuzzy linguistic matrix, there are three kinds of fuzzy relationships between terms, i.e., similar relation, hierarchical relation, and associative relation. The implicit fuzzy relationships between terms are inferred by the transitive closure of the fuzzy linguistic matrix based on fuzzy theory. And the proposed method has the capability to deal with a qualitative linguistic weights in a query and in indexing of information items to reflect qualitative measure of human based on vague and uncertain decisions rather than a quantitiative measure. Therefore the proposed method is more flexible than the ones presented in papers[1-3]. Moreover our method is more effectual of time than the ones presented in papers[1-3] because we use a fuzzy linguistic matrix and AON (Associate Ordinary Number) values in query evaluation process. As a result, the proposed method allows the users to perform fuzzy queries in a more flexible and more intelligent manner.

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Facet Query Expansion with an Object-Based Thesaurus in Reusable Component Retrieval Systems (재사용 부품 검색 시스템에서 객체기반 시소러스를 이용한 패싯 질의의 확장)

  • Choi, Jae-Hun;Kim, Ki-Heon;Yang, Jae-Dong;Lee, Dong-Gil
    • Journal of KIISE:Software and Applications
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    • v.27 no.2
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    • pp.168-179
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    • 2000
  • In reusable component retrieval systems with facet-based schemes, facet queries are generally used for representing the characteristics of components relevant to users. This paper proposes an expanded facet query equipped with an object-based thesaurus to precisely formulate user's intents. To evaluate the query, a component retrieval system is also designed and implemented. For exactly retrieving the components, user's query should include relevant facet values capable of fully specifying their characteristics. However, simply listing a series of facet values directly inputted by users, conventional queries fails to precisely represent user's intents. Our query, called expanded facet query, employs fuzzy boolean operators and object-based thesaurus; the former logically expresses the fuzzy connectives between facet queries and required components, whereas the latter helps users appropriately select the specific facet values into the query. A thesaurus query is provided to recommend the relevant facet values with their fuzzy degrees from the thesaurus as well. Furthermore, our retrieval system can automatically formulate queries with the recommended facet values, if necessary.

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Intelligent Query Analysis using Fuzzy Association Rule (퍼지 연관규칙을 이용한 지능적 질의해석)

  • Kim, Mi-Hye
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.6
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    • pp.2214-2218
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    • 2010
  • Association rule is one of meaning and useful extraction methods from large amounts of data, and furnish useful information to user for data describing a pattern or similarity among attributes in database. Association rule have been studied about existence and nonexistence rule in boolean database. In this paper, we propose an intelligent query system using fuzzy association rule by extraction association rule changing a quantitative attribute data to a nominal attribute value.

An Extended Concept-based Image Retrieval System : E-COIRS (확장된 개념 기반 이미지 검색 시스템)

  • Kim, Yong-Il;Yang, Jae-Dong;Yang, Hyoung-Jeong
    • Journal of KIISE:Computing Practices and Letters
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    • v.8 no.3
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    • pp.303-317
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    • 2002
  • In this paper, we design and implement E-COIRS enabling users to query with concepts and image features used for further refining the concepts. For example, E-COIRS supports the query "retrieve images containing black home appliance to north of reception set. "The query includes two types of concepts: IS-A and composite. "home appliance"is an IS-A concept, and "reception set" is a composite concept. For evaluating such a query. E-COIRS includes three important components: a visual image indexer, thesauri and a query processor. Each pair of objects in an mage captured by the visual image indexer is converted into a triple. The triple consists of the two object identifiers (oids) and their spatial relationship. All the features of an object is referenced by its old. A composite concept is detected by the triple thesaurus and IS-A concept is recolonized by the fuzzy term thesaurus. The query processor obtains an image set by matching each triple in a user with an inverted file and CS-Tree. To support efficient storage use and fast retrieval on high-dimensional feature vectors, E-COIRS uses Cell-based Signature tree(CS-Tree). E-COIRS is a more advanced content-based image retrieval system than other systems which support only concepts or image features.

Comparing object images using fuzzy-logic induced Hausdorff Distance (퍼지 논리기반 HAUSDORFF 거리를 이용한 물체 인식)

  • 강환일
    • Journal of Intelligence and Information Systems
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    • v.6 no.1
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    • pp.65-72
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    • 2000
  • In this paper we propose the new binary image matching algorithm called the Fuzzy logic induced Hausdorff Distance(FHD) for finding the maximally matched image with the query image. The membership histogram is obtained by normalizing the cardinality of the subset with the corresponding radius after obtaining the distribution of the minimum distance computed by the Hausdroff distance between two binary images. in the proposed algorithm, The fuzzy influence method Center of Gravity(COG) is applied to calculate the best matching candidate in the membership function described above. The proposed algorithm shows the excellent results for the face image recognition when the noise is added to the query image as well as for the character recognition.

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Performance Evaluation of Fuzzy Thesaurus for Component Retrieval (컴포넌트 검색을 위한 퍼지 시소러스의 성능 평가)

  • 채은주;한정수;김귀정
    • Proceedings of the Korea Contents Association Conference
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    • 2003.05a
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    • pp.411-415
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    • 2003
  • This paper compared fuzzy thesaurus through query extension with existent thesaurus and direct matching retrieval etc. Performance of fuzzy thesaurus is evaluated by the recall and precision through simulation. An experiment did through assessment that use critical value, query extension, and reusability satisfaction. As a result of the experiment, we knew component retrieval efficiency of fuzzy thesaurus excels.

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Hybrid Fuzzy Association Structure for Robust Pet Dog Disease Information System

  • Kim, Kwang Baek;Song, Doo Heon;Jun Park, Hyun
    • Journal of information and communication convergence engineering
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    • v.19 no.4
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    • pp.234-240
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    • 2021
  • As the number of pet dog-related businesses is rising rapidly, there is an increasing need for reliable pet dog health information systems for casual pet owners, especially those caring for older dogs. Our goal is to implement a mobile pre-diagnosis system that can provide a first-hand pre-diagnosis and an appropriate coping strategy when the pet owner observes abnormal symptoms. Our previous attempt, which is based on the fuzzy C-means family in inference, performs well when only relevant symptoms are provided for the query, but this assumption is not realistic. Thus, in this paper, we propose a hybrid inference structure that combines fuzzy association memory and a double-layered fuzzy C-means algorithm to infer the probable disease with robustness, even when noisy symptoms are present in the query provided by the user. In the experiment, it is verified that our proposed system is more robust when noisy (irrelevant) input symptoms are provided and the inferred results (probable diseases) are more cohesive than those generated by the single-phase fuzzy C-means inference engine.

Fuzzy Query Processing through Two-level Similarity Relation Matrices Construction (2계층 유사관계행렬 구축을 통한 질의 처리)

  • 이기영
    • Journal of the Korea Computer Industry Society
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    • v.4 no.10
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    • pp.587-598
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    • 2003
  • This paper construct two-level word similarity relation matrices about title and to scientific treatise. As guide keyword similarity relation matrices which is constructed to co-occurrence frequency base same time keeps recall rater by query expansion by tolerance relation, it is index structure to improve the precision rate by two-level contents base retrieval. Therefore, draw area knowledge through subject analysis and reasoned user's information request and area knowledge to fuzzy logic base. This research is research to improve vocabulary mismatch problem and information expression having essentially on query.

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An Intellingnet Query Processing System for Relational Database System (관계형 데이타베이스 시스템을 위한 지능적인 질의처리시스템)

  • 김대수;김창석
    • Journal of the Korean Institute of Intelligent Systems
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    • v.7 no.4
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    • pp.1-8
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    • 1997
  • In this paper, we propose a new intelligent query processing system for relational database !systems. By analyzing previous research results related with fuzzy queries, a new intelligent query processing sysytem is developed and the role of each module including intelligent query processor is defined and :some algorithms for parser, query translation module, inference engine, semantic DB and result com-poser are suggested. By applying a typical example to the proposed intelligent query processing liysytem, reasonable results for the ambiguous query are drawn, and therefore it shows a promising model returning ordered result for both the ambiguous queries and general queries.

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A Naming Application Model for Sensor Networks (센서 네트워크를 위한 네이밍 응용 모델)

  • Kim, Young-Jun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.10 no.11
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    • pp.3183-3192
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    • 2009
  • The purpose of this paper is to introduce Naming application model for sensor networks. Currently, sensor networks comprised of sensor nodes have provided an application range which could not function before. However, unlike general network, current sensor networks are designed to cooperate with major wireless-capable sensor devices with limited resources. Thus, exporting/importing between individual sensor and current sensor networks is very inefficient and unstable. Attribute, schema and DIT(Directory Information Tree) must be designed for sensor network using SN LDAP application model in order to maintain transparency and provide constant service in a situation of data defect. With the system explained as above, Naming application model is made to manage SN Fuzzy Query. It shall be more efficient and stable structure as long as Naming application using a virtual equation in a certain environment with information collected from sensor node is provided. In this paper, I would like to introduce SN Fuzzy LDAP model for sensor network by quick Naming method. Also, naming application which is possible for fuzzy query in a certain environment based on the system will be proved.