• Title/Summary/Keyword: Intelligent query

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Music Search Algorithm for Automotive Infotainment System (자동차 환경의 인포테인먼트 시스템을 위한 음악 검색 알고리즘)

  • Kim, Hyoung-Gook;Kim, Jae-Man
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.12 no.1
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    • pp.81-87
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    • 2013
  • In this paper, we propose a music search algorithm for automotive infotainment system. The proposed method extracts fingerprints using the high peaks based on log-spectrum of the music signal, and the extracted music fingerprints store in cloud server applying a hash value. In the cloud server, the most similar music is retrieved by comparing the user's query music with the fingerprints stored in hash table of cloud server. To evaluate the performance of the proposed music search algorithm, we measure an accuracy of the retrieved results according to various length of the query music and measure a retrieval time according to the number of stored music database in hash table.

Indexing of XML with B+-tree (B+-tree를 이용한 XML 색인기법)

  • Kwon, Guk-Bong;Hong, Dong-Kweon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.1
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    • pp.94-100
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    • 2006
  • Computing paradigm shift to internet-based one has accelerated the use of XML in diverse applications. This phenomena has made the explosive increases of XML data and it triggered many active researches in maintaining very huge amount of XML data in turn. In this paper we present a persistent graph-based XML indexing lot data-centric XML data. In our approach we use 3 graphs to represent XML indexes and XML data itself. They are schema graph, data graph index. And then we have mapped those graphs to B+-trees the persistency. With our approach we can achieve linear query execution time with the increase of XML sizes.

Knowledge-based Semantic Meta-Search Engine (지식기반 의미 메타 검색엔진)

  • Lee, In-K.;Son, Seo-H.;Kwon, Soon-H.
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.6
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    • pp.737-744
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    • 2004
  • Retrieving relevant information well corresponding to the user`s request from web is a crucial task of search engines. However, most of conventional search engines based on pattern matching schemes to queries have a limitation that is not easy to provide results corresponding to the user`s request due to the uncertainty of queries. To overcome the limitation in this paper, we propose a framework for knowledge-based semantic meta-search engines with the following five processes: (i) Query formation, (ii) Query expansion, (iii) Searching, (iv) Ranking recreation, and (v) Knowledge base. From simulation results on english-based web documents, we can see that the Proposed knowledge-based semantic meta-search engine provides more correct and better searching results than those obtained by using the Google.

Research on a Logical Agent Communication Language for Multi-Agent Systems Negotiation (I) (멀티-에이전트 시스템 협상을 위한 논리적인 에이전트 통신 언어에 관한 연구 (I))

  • Lee, Myung-Jin;Han, Hyun-Kwan
    • Journal of Internet Computing and Services
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    • v.8 no.1
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    • pp.115-123
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    • 2007
  • Agents in Multi-Agent System; (MAS) should make use of a common Agent Communication Language (ACL) in order to negotiate with others, and conform to negotiation protocols thatare designed to reach agreements. Therefore, agents must have suitable architectures that could cover above requirements. In this paper, we define an instructive ACL and compare it with other ACLs such as Foundation for Intelligent Physical Agents (FIPA) ACL and Knowledge Query Manipulation Language(KQML), In particular, we represent agents as logic programs with knowledge base and negotiation library. Finally, we show how the planner, which is in the negotiation library, provides the plan of actions and updates agent's knowledge base.

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Implementation of Search Method based on Sequence and Adjacency Relationship of User Query (사용자 검색 질의 단어의 순서 및 단어간의 인접 관계에 기반한 검색 기법의 구현)

  • So, Byung-Chul;Jung, Jin-Woo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.6
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    • pp.724-729
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    • 2011
  • Information retrieval is a method to search the needed data by users. Generally, when a user searches some data in the large scale data set like the internet, ranking-based search is widely used because it is not easy to find the exactly needed data at once. In this paper, we propose a novel ranking-based search method based on sequence and adjacency relationship of user query by the help of TF-IDF and n-gram. As a result, it was possible to find the needed data more accurately with 73% accuracy in more than 19,000 data set.

Semantic Information Retrieval Based on User-Word Intelligent Network (U-WIN 기반의 의미적 정보검색 기술)

  • Im, Ji-Hui;Choi, Ho-Seop;Ock, Cheol-Young
    • Proceedings of the Korea Contents Association Conference
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    • 2006.11a
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    • pp.547-550
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    • 2006
  • The criterion which judges an information retrieval system performance is to how many accurately retrieve an information that the user wants. The search result which uses only homograph has been appears the various documents that relates to each meaning of the word or intensively appears the documents that relates to specific meaning of it. So in this paper, we suggest semantic information retrieval technique using relation within User-Word Intelligent Network(U-WIN) to solve a disambiguation of query In our experiment, queries divide into two classes, the homograph used in terminology and the general homograph, and it sets the expansion query forms at "query + hypemym". Thus we found that only web document search's precision is average 73.5% and integrated search's precision is average 70% in two portal site. It means that U-WIN-Based semantic information retrieval technique can be used efficiently for a IR system.

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Cluster-Based Selection of Diverse Query Examples for Active Learning (능동적 학습을 위한 군집화 기반의 다양한 복수 문의 예제 선정 방법)

  • Kang, Jae-Ho;Ryu, Kwang-Ryel;Kwon, Hyuk-Chul
    • Journal of Intelligence and Information Systems
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    • v.11 no.1
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    • pp.169-189
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    • 2005
  • In order to derive a better classifier with a limited number of training examples, active teaming alternately repeats the querying stage fur category labeling and the subsequent learning stage fur rebuilding the calssifier with the newly expanded training set. To relieve the user from the burden of labeling, especially in an on-line environment, it is important to minimize the number of querying steps as well as the total number of query examples. We can derive a good classifier in a small number of querying steps by using only a small number of examples if we can select multiple of diverse, representative, and ambiguous examples to present to the user at each querying step. In this paper, we propose a cluster-based batch query selection method which can select diverse, representative, and highly ambiguous examples for efficient active learning. Experiments with various text data sets have shown that our method can derive a better classifier than other methods which only take into account the ambiguity as the criterion to select multiple query examples.

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Processing of ρ-intersect Operation on RDF Data Using Suffix Array (RDF 데이터에서 접미사 배열을 이용한 ρ-intersect 연산의 처리)

  • Kim, Sung-Wan;Kim, Youn-Hee
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.7
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    • pp.95-103
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    • 2011
  • The actual utilization of Semantic Web technology which aims to provide more intelligent and automated service for information retrieval over the Web becomes gradually reality. RDF is widely used as the one of standard formats to present and manage the voluminous data on the Web. Efficient query processing on RDF data, therefore, is one of the ongoing research topics. Retrieving resources having a specific association from a given resource is the typical query processing type and several researches for this have done. However the most of previous researches have not fully considered discovering the complex relationship among resources such as returning the association between resources as the query processing result. This paper introduces the indexing and query processing for ${\rho}$-intersect operation which is one of the semantic association retrieval types. It includes an indexing scheme using suffix array and optimal processing approaches for handling ${\rho}$-intersect operation. The experimental evaluations shows that the average execution times for the proposed approach is 3~7 times faster than the previous approach.

Fuzzy Theory based Electronic Commerce Navigation Agent that can Process Natural Language (자연어 처리가 가능한 퍼지 이론 기반 전자상거래 검색 에이전트)

  • 김명순;정환묵
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.3
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    • pp.246-251
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    • 2001
  • In this paper, we proposed the intelligent navigation agent model for successive electronic commerce system management. Fuzzy theory is very useful method where keywords have vague conditions and system must process that conditions. So, using fuzzy theory, we proposed the model that can process the vague keywords effectively. Through the this, we verified that we can get the more appropriate navigation result than any other crisp retrieval keywords condition.

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Design and Research for Intelligent Typhoon Evasion System for Ships

  • Wang, Jing-Quan;He, Yi;Shi, Ping-An;Peng, Xiao-Hong;Xu, Zu-Yuan;Qin, Shan-Ci;Li, Qing-Lie;Ding, Bing-Lin
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2001.10a
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    • pp.177-186
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    • 2001
  • Based upon the previous experiences and typical oases of typhoon evasion fur ships as well as tile achievement in scientific research in this detrain, we developed the Intelligent Typhoon Evasion System for Ships. It consists of five subsystems, including electronic charts, ship movement management, typhoon information query and automatic plotting, real-time calculation of ship-typhoon situation, intelligent typhoon evasion decision making. With the synthetical application of analogy theory, synoptic chart, satellite cloud picture analysis, typhoon digital forecast and other relevant technologies, we leave established the typhoon evasion data bases. model bases and knowledge bases, which make it possible to automatically track the ships and typhoon paths. The system can realize ship-typhoon situation analysis, risk levee assessment, typhoon paths correction and course synoptic forecast, and intelligent typhoon evasion decision making.

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