• Title/Summary/Keyword: boolean model

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Boolean Query Formulation From Korean Natural Language Queries using Syntactic Analysis (구문분석에 기반한 한글 자연어 질의로부터의 불리언 질의 생성)

  • Park, Mi-Hwa;Won, Hyeong-Seok;Lee, Geun-Bae
    • Journal of KIISE:Software and Applications
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    • v.26 no.10
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    • pp.1219-1229
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    • 1999
  • 일반적으로 AND, OR, NOT과 같은 연산자를 사용하는 불리언 질의는 사용자의 검색의도를 정확하게 표현할 수 있기 때문에 검색 전문가들은 불리언 질의를 사용하여 높은 검색성능을 얻는다고 알려져 있지만, 일반 사용자는 자신이 원하는 정보를 불리언 형태로 표현하는데 익숙하지 않다. 본 논문에서는 검색성능의 향상과 사용자 편의성을 동시에 만족하기 위하여 사용자의 자연어 질의를 확장 불리언 질의로 자동 변환하는 방법론을 제안한다. 먼저 자연어 질의를 범주문법에 기반한 구문분석을 수행하여 구문트리를 생성하고 연산자 및 키워드 정보를 추출하여 구문트리를 간략화한다. 다음으로 간략화된 구문트리로부터 명사구를 합성하고 키워드들에 대한 가중치를 부여한 후 불리언 질의를 생성하여 검색을 수행한다. 또한 구문분석의 오류로 인한 검색성능 저하를 최소화하기 위하여 상위 N개 구문트리에 대해 각각 불리언 질의를 생성하여 검색하는 N-BEST average 방법을 제안하였다. 정보검색 실험용 데이타 모음인 KTSET2.0으로 실험한 결과 제안된 방법은 수동으로 추출한 불리언 질의보다 8% 더 우수한 성능을 보였고, 기존의 벡터공간 모델에 기반한 자연어질의 시스템에 비해 23% 성능향상을 보였다. Abstract There have been a considerable evidence that trained users can achieve a good search effectiveness through a boolean query because a structural boolean query containing operators such as AND, OR, and NOT can make a more accurate representation of user's information need. However, it is not easy for ordinary users to construct a boolean query using appropriate boolean operators. In this paper, we propose a boolean query formulation method that automatically transforms a user's natural language query into a extended boolean query for both effectiveness and user convenience. First, a user's natural language query is syntactically analyzed using KCCG(Korean Combinatory Categorial Grammar) parser and resulting syntactic trees are structurally simplified using a tree-simplifying mechanism in order to catch the logical relationships between keywords. Next, in a simplified tree, plausible noun phrases are identified and added into the same tree as new additional keywords. Finally, a simplified syntactic tree is automatically converted into a boolean query using some mapping rules and linguistic heuristics. We also propose an N-BEST average method that uses top N syntactic trees to compensate for bad effects of single incorrect top syntactic tree. In experiments using KTSET2.0, we showed that a proposed method outperformed a traditional vector space model by 23%, and surprisingly manually constructed boolean queries by 8%.

Probability subtraction method for accurate quantification of seismic multi-unit probabilistic safety assessment

  • Park, Seong Kyu;Jung, Woo Sik
    • Nuclear Engineering and Technology
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    • v.53 no.4
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    • pp.1146-1156
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    • 2021
  • Single-unit probabilistic safety assessment (SUPSA) has complex Boolean logic equations for accident sequences. Multi-unit probabilistic safety assessment (MUPSA) model is developed by revising and combining SUPSA models in order to reflect plant state combinations (PSCs). These PSCs represent combinations of core damage and non-core damage states of nuclear power plants (NPPs). Since all these Boolean logic equations have complemented gates (not gates), it is not easy to generate exact Boolean solutions. Delete-term approximation method (DTAM) has been widely applied for generating approximate minimal cut sets (MCSs) from the complex Boolean logic equations with complemented gates. By applying DTAM, approximate conditional core damage probability (CCDP) has been calculated in SUPSA and MUPSA. It was found that CCDP calculated by DTAM was overestimated when complemented gates have non-rare events. Especially, the CCDP overestimation drastically increases if seismic SUPSA or MUPSA has complemented gates with many non-rare events. The objective of this study is to suggest a new quantification method named probability subtraction method (PSM) that replaces DTAM. The PSM calculates accurate CCDP even when SUPSA or MUPSA has complemented gates with many non-rare events. In this paper, the PSM is explained, and the accuracy of the PSM is validated by its applications to a few MUPSAs.

Document ranking methods using term dependencies from a thesaurus (시소러스의 연관성 정보를 이용한 문서의 순위 결정 방법)

  • 이준호
    • Journal of the Korean Society for information Management
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    • v.10 no.2
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    • pp.3-22
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    • 1993
  • In recent years various document ranking methods such as Relevance. R-Distance and K-Distance have been developed wh~ch can be used in thesaurus-based boolean retrieval systems. They give high quality document rankings in many cases by using term dependence lnformatlon from a thesaurus. However, they suffer from several problems resulting from inefficient and Ineffective evaluation of boolean operators AND. OR and NOT. In this paper we propose new thesaurus-based document ranking methods called KB-FSM and KB-EBM by exploitmg the enhanced fuzzy set model and the extended boolean model. The proposed methods overcome the problems of the previous methods and use term dependencies from a thesaurs effectively. We also show through performance comparison that KB-FSM and KBEBM provide higher retrieval effectiveness than Relevance. R-D~stance and K-Distance.

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Impact of Sensing Models on Probabilistic Blanket Coverage in Wireless Sensor Network (무선 센서 네트워크에서 Probabilistic Blanket Coverage에 대한 센싱 모델의 영향)

  • Pudasaini, Subodh;Kang, Moon-Soo;Shin, Seok-Joo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.7A
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    • pp.697-705
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    • 2010
  • In Wireless Sensor Networks (WSNs), blanket (area) coverage analysis is generally carried to find the minimum number of active sensor nodes required to cover a monitoring interest area with the desired fractional coverage-threshold. Normally, the coverage analysis is performed using the stochastic geometry as a tool. The major component of such coverage analysis is the assumed sensing model. Hence, the accuracy of such analysis depends on the underlying assumption of the sensing model: how well the assumed sensing model characterizes the real sensing phenomenon. In this paper, we review the coverage analysis for different deterministic and probabilistic sensing models like Boolean and Shadow-fading model; and extend the analysis for Exponential and hybrid Boolean-Exponential model. From the analytical performance comparison, we demonstrate the redundancy (in terms of number of sensors) that could be resulted due to the coverage analysis based on the detection capability mal-characterizing sensing models.

The Effects of Feedback Loops on the Network Robustness by using a Random Boolean Network Model (랜덤 불리언 네트워크 모델을 이용한 되먹임 루프가 네트워크 강건성에 미치는 영향)

  • Kwon, Yung-Keun
    • Journal of KIISE:Computer Systems and Theory
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    • v.37 no.3
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    • pp.138-146
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    • 2010
  • It is well known that many biological networks are very robust against various types of perturbations, but we still do not know the mechanism of robustness. In this paper, we find that there exist a number of feedback loops in a real biological network compared to randomly generated networks. Moreover, we investigate how the topological property affects network robustness. To this end, we properly define the notion of robustness based on a Boolean network model. Through extensive simulations, we show that the Boolean networks create a nearly constant number of fixed-point attractors, while they create a smaller number of limit-cycle attractors as they contain a larger number of feedback loops. In addition, we elucidate that a considerably large basin of a fixed-point attractor is generated in the networks with a large number of feedback loops. All these results imply that the existence of a large number of feedback loops in biological networks can be a critical factor for their robust behaviors.

An implementation of CSG modeling technique on Machining Simulation using C++ and Open GL

  • Le, Duy;Kim, Su-Jin;Lee, Jong-Min;Nguyen, Anh-Thi;Ha, Vy-Thoai
    • Proceedings of the KSME Conference
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    • 2008.11a
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    • pp.1053-1056
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    • 2008
  • An application of CSG (Constructive Solid Geometry) modeling technique in Machining Simulation is introduced in this paper. The current CSG model is based on z-buffer CSG Rendering Algorithm. In order to build a CSG model, frame buffers of VGA (Video Graphic Accelerator) should be used in term of color buffer, depth buffer, and stencil buffer. In addition to using CSG model in machine simulation Stock and Cutter Swept Surface (CSS) should be solid. Method to create a solid Cuboid stock and Ball-end mill CSS are included in the present paper. Boolean operations are used to produce the after-cut part, especially the Difference operation between Stock and CSS as the cutter remove materials form stock. Finally, a small program called MaSim which simulates one simple cut using this method was created.

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A Study on Document Retrieval of Web Using Relevance Feedback (적합성 피드백을 이용한 웹 문서검색에 관한 연구)

  • 김영천;이성주
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.5 no.3
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    • pp.597-604
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    • 2001
  • In conventional boolean retrieval systems, document ranking is not supported and similarity coefficients cannot be computed between queries and documents. The MMM, Paice and P-norm models have been proposed in the past to support the ranking facility for boolean retrieval systems. They have common properties of interpreting boolean operators softly. In this paper we propose a new soft evaluation method for Information retrieval using query splitting relevance feedback model. We also show through performance comparison that query splitting relevance feedback(QSRF) is more efficient and effective than MMM, Paice and P-norm.

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A Study on Information Retrieval Using Query Splitting Relevance Feedback (질의분해 적합성 피드백을 이용한 정보검색에 관한 연구)

  • 김영천;박병권;이성주
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.3
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    • pp.252-257
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    • 2001
  • In conventional boolean retrieval systems, document ranking is not supported and similarity coefficients cannot be computed between queries and documents. The MMM, Paice and P-norm models have been proposed in the past to support the ranking facility for boolean retrieval systems. They have common properties of interpreting boolean operators softly. In this paper we propose a new soft evaluation method for Information retrieval using query splitting relevance feedback model. We also show through performance comparison that query splitting relevance feedback(QSRF) is more efficient and effective than MMM, Paice and P-norm.

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A Study on Feature-Based Multi-Resolution Modelling - Part I: Effective Zones of Features (특징형상기반 다중해상도 모델링에 관한 연구 - Part I: 특징형상의 유효영역)

  • Lee K.Y.;Lee S.H.
    • Korean Journal of Computational Design and Engineering
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    • v.10 no.6
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    • pp.432-443
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    • 2005
  • Recent three-dimensional feature-based CAD systems based on solid or non-manifold modelling functionality have been widely used for product design in manufacturing companies. When product models associated with features are used in various downstream applications such as analysis, however, simplified and abstracted models at various levels of detail (LODs) are frequently more desirable and useful than the full detailed model. To provide multi-resolution models, the features need to be rearranged according to a criterion that measures the significance of the feature. However, if the features are rearranged, the resulting shape is possibly different from the original because union and subtraction Boolean operations are not commutative. To solve this problem, in this paper, the new concept of the effective zone of a feature is defined and identified using Boolean algebra. By introducing the effective zone, an arbitrary rearrangement of features becomes possible and arbitrary LOD criteria may be selected to suit various applications. Besides, because the effective zone of a feature is independent of the data structure of the model, the multi-resolution modelling algorithm based on the effective zone can be implemented on any 3D CAD system based on conventional solid representations as well as non-manifold topological (NMT) representations.

A New Quantification Method for Multi-Unit Probabilistic Safety Assessment (다수기 PSA 수행을 위한 새로운 정량화 방법)

  • Park, Seong Kyu;Jung, Woo Sik
    • Journal of the Korean Society of Safety
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    • v.35 no.1
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    • pp.97-106
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    • 2020
  • The objective of this paper is to suggest a new quantification method for multi-unit probabilistic safety assessment (PSA) that removes the overestimation error caused by the existing delete-term approximation (DTA) based quantification method. So far, for the actual plant PSA model quantification, a fault tree with negates have been solved by the DTA method. It is well known that the DTA method induces overestimated core damage frequency (CDF) of nuclear power plant (NPP). If a PSA fault tree has negates and non-rare events, the overestimation in CDF drastically increases. Since multi-unit seismic PSA model has plant level negates and many non-rare events in the fault tree, it should be very carefully quantified in order to avoid CDF overestimation. Multi-unit PSA fault tree has normal gates and negates that represent each NPP status. The NPP status means core damage or non-core damage state of individual NPPs. The non-core damage state of a NPP is modeled in the fault tree by using a negate (a NOT gate). Authors reviewed and compared (1) quantification methods that generate exact or approximate Boolean solutions from a fault tree, (2) DTA method generating approximate Boolean solution by solving negates in a fault tree, and (3) probability calculation methods from the Boolean solutions generated by exact quantification methods or DTA method. Based on the review and comparison, a new intersection removal by probability (IRBP) method is suggested in this study for the multi-unit PSA. If the IRBP method is adopted, multi-unit PSA fault tree can be quantified without the overestimation error that is caused by the direct application of DTA method. That is, the extremely overestimated CDF can be avoided and accurate CDF can be calculated by using the IRBP method. The accuracy of the IRBP method was validated by simple multi-unit PSA models. The necessity of the IRBP method was demonstrated by the actual plant multi-unit seismic PSA models.