• Title/Summary/Keyword: Query process

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Cooperative Case-based Reasoning Using Approximate Query Answering (근사질의 응답기능을 이용한 협동적 사례기반추론)

  • 김진백
    • The Journal of Information Systems
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    • v.8 no.1
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    • pp.27-44
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    • 1999
  • Case-Based Reasoning(CBR) offers a new approach for developing knowledge based systems. CBR has several research issues which can be divided into two categories : (1) static issues and (2) dynamic issues. The static issues are related to case representation scheme and case data model, that is, focus on casebase which is a repository of cases. The dynamic issues, on the other hand, are related to case retrieval procedure and problem solving process, i.e. case adaptation phase. This research is forcused on retrieval procedure Traditional query processing accepts precisely specified queries and only provides exact answers, thus requiring users to fully understand the problem domain and the casebase schema, but returning limited or even null information if the exact answer is not available. To remedy such a restriction, extending the classical notion of query answering to approximate query answering(AQA) has been explored. AQA can be achieved by neighborhood query answering or associative query answering. In this paper, neighborhood query answering technique is used for AQA. To reinforce the CBR process, a new retrieval procedure(cooperative CBR) using neighborhood query answering is proposed. An neighborhood query answering relaxes a query scope to enlarge the search range, or relaxes an answer scope to include additional information. Computer Aided Process Planning(CAPP) is selected as cooperative CBR application domain for test. CAPP is an essential key for achieving CIM. It is the bridge between CAD and CAM and translates the design information into manufacturing instructions. As a result of the test, it is approved that the problem solving ability of cooperative CBR is improved by relaxation technique.

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Automatic Suggestion for PubMed Query Reformulation

  • Tuan, Luu Anh;Kim, Jung-Jae
    • Journal of Computing Science and Engineering
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    • v.6 no.2
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    • pp.161-167
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    • 2012
  • Query reformulation is an interactive process of revising user queries according to the query results. To assist biomedical researchers in this process, we present novel methods for automatically generating query reformulation suggestions. While previous work on query reformulation focused on addition of words to user queries, our method can deal with three types of query reformulation (i.e., addition, removal and replacement). The accuracy of the method for the addition type is ten times better than PubMed's "Also try", while the execution time is short enough for practical use.

A Method for k Nearest Neighbor Query of Line Segment in Obstructed Spaces

  • Zhang, Liping;Li, Song;Guo, Yingying;Hao, Xiaohong
    • Journal of Information Processing Systems
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    • v.16 no.2
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    • pp.406-420
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    • 2020
  • In order to make up the deficiencies of the existing research results which cannot effectively deal with the nearest neighbor query based on the line segments in obstacle space, the k nearest neighbor query method of line segment in obstacle space is proposed and the STA_OLkNN algorithm under the circumstance of static obstacle data set is put forward. The query process is divided into two stages, including the filtering process and refining process. In the filtration process, according to the properties of the line segment Voronoi diagram, the corresponding pruning rules are proposed and the filtering algorithm is presented. In the refining process, according to the relationship of the position between the line segments, the corresponding distance expression method is put forward and the final result is obtained by comparing the distance. Theoretical research and experimental results show that the proposed algorithm can effectively deal with the problem of k nearest neighbor query of the line segment in the obstacle environment.

Efficient Temporal Query Processing using Materialized View (형성 뷰를 이용한 효율적인 시간지원 질의 처리 기법)

  • 정경자
    • Journal of the Korea Society of Computer and Information
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    • v.3 no.4
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    • pp.1-9
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    • 1998
  • Temporal Databases store all of informations by time varying, so the temporal query processor has to process very large information. Therefore, we propose an efficient method of query processing by using the relevance checking algorithm of input query and view definition. The relevance checking algorithm of query investigates relevance between the input query of user about base relation and the execution tree of view definition stored in system catalog. And related input query with view definition have a process of the query translation to the execution tree of view. So temporal query processor is able to increase performance of query processor by reducing the number of tuple.

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Extracting Database Knowledge from Query Trees

  • 윤종필
    • Journal of Electrical Engineering and information Science
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    • v.1 no.2
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    • pp.146-146
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    • 1996
  • Although knowledge discovery is increasingly important in databases, the discovered knowledge sets may not be effectively used for application domains. It is partly because knowledge discovery does not take user's interests into account, and too many knowledge sets are discovered to handle efficiently. We believe that user's interests are conveyed by a query and if a nested query is concerned it may include a user's thought process. This paper describes a novel concept for discovering knowledge sets based on query processing. Knowledge discovery process is performed by: extracting features from databases, spanning features to generate range features, and constituting a knowledge set. The contributions of this paper include the following: (1) not only simple queries but also nested queries are considered to discover knowledge sets regarding user's interests and user's thought process, (2) not only positive examples (answer to a query) but also negative examples are considered to discover knowledge sets regarding database abstraction and database exceptions, and (3) finally, the discovered knowledge sets are quantified.

Extracting Database Knowledge from Query Trees

  • Yoon, Jongpil
    • Journal of Electrical Engineering and information Science
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    • v.1 no.2
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    • pp.145-156
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    • 1996
  • Although knowledge discovery is increasingly important in databases, the discovered knowledge sets may not be effectively used for application domains. It is partly because knowledge discovery does not take user's interests into account, and too many knowledge sets are discovered to handle efficiently. We believe that user's interests are conveyed by a query and if a nested query is concerned it may include a user's thought process. This paper describes a novel concept for discovering knowledge sets based on query processing. Knowledge discovery process is performed by: extracting features from databases, spanning features to generate range features, and constituting a knowledge set. The contributions of this paper include the following: (1) not only simple queries but also nested queries are considered to discover knowledge sets regarding user's interests and user's thought process, (2) not only positive examples (answer to a query) but also negative examples are considered to discover knowledge sets regarding database abstraction and database exceptions, and (3) finally, the discovered knowledge sets are quantified.

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CONTINUOUS QUERY PROCESSING IN A DATA STREAM ENVIRONMENT

  • Lee, Dong-Gyu;Lee, Bong-Jae;Ryu, Keun-Ho
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.3-5
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    • 2007
  • Many continuous queries are important to be process efficiently in a data stream environment. It is applied a query index technique that takes linear performance irrespective of the number and width of intervals for processing many continuous queries. Previous researches are not able to support the dynamic insertion and deletion to arrange intervals for constructing an index previously. It shows that the insertion and search performance is slowed by the number and width of interval inserted. Many intervals have to be inserted and searched linearly in a data stream environment. Therefore, we propose Hashed Multiple Lists in order to process continuous queries linearly. Proposed technique shows fast linear search performance. It can be utilized the systems applying a sensor network, and preprocessing technique of spatiotemporal data mining.

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Design and Implementation of Spatiotemporal Query Processing Systems (시공간 질의 처리 시스템의 설계 및 구현)

  • Lee, Seong-Jong;Kim, Dong-Ho;Ryu, Geun-Ho
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.5
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    • pp.1166-1176
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    • 1999
  • The spationtemporal databases support a historical informations as well as spatial managements for various kinds of objects in the real world, and can be efficiently used in many applications such as geographic information system, urban plan system, car navigation system. However it is difficult to represent efficiently historical operations with conventional database query language for spatial objects. In terms of cost for query processing, it also degenerates performance of query processing because of syntactic limitations which is innate in conventional query representation. So in this paper, we introduce a new query language, entitled as STQL, which has been extended on the basis of the most popular relational database query language SQL. And we implement as well as evaluate a spationtemporal query processing system that get a query written by STQL and then process it in a main memory.

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Spatial Query Processing Based on Minimum Bounding in Wireless Sensor Networks

  • Yang, Sun-Ok;Kim, Sung-Suk
    • Journal of Information Processing Systems
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    • v.5 no.4
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    • pp.229-236
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    • 2009
  • Sensors are deployed to gather physical, environmental data in sensor networks. Depending on scenarios, it is often assumed that it is difficult for batteries to be recharged or exchanged in sensors. Thus, sensors should be able to process users' queries in an energy-efficient manner. This paper proposes a spatial query processing scheme- Minimum Bounding Area Based Scheme. This scheme has a purpose to decrease the number of outgoing messages during query processing. To do that, each sensor has to maintain some partial information locally about the locations of descendent nodes. In the initial setup phase, the routing path is established. Each child node delivers to its parent node the location information including itself and all of its descendent nodes. A parent node has to maintain several minimum bounding boxes per child node. This scheme can reduce unnecessary message propagations for query processing. Finally, the experimental results show the effectiveness of the proposed scheme.

An Efficient Query Processing in Stream DBMS using Query Preprocessor (질의 전처리기를 사용한 스트림 DBMS의 효율적 질의처리)

  • Yang, Young-Hyoo
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.1
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    • pp.65-73
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    • 2008
  • The telematics data management deals with queries on stream data coming from moving cars. So the stream DBMS should process the large amount of data stream in real-time. In this article, previous research projects are analyzed in the aspects of query processing. And a hybrid model is introduced where query preprocessor is used to process all types of queries in one singe system. Decreasing cost and rapidly increasing Performance of devices may guarantee the utmost parallelism of the hybrid system. As a result, various types of stream DBMS queries could be processed in a uniform and efficient way in a single system.

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