簡易檢索 / 詳目顯示

研究生: 劉爾剛
Er-Gang Liu
論文名稱: 關聯式資料庫之關鍵字查詢處理技術
The Query Processing Techniques for Keyword Search in Relational Database
指導教授: 柯佳伶
Koh, Jia-Ling
學位類別: 碩士
Master
系所名稱: 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年: 2013
畢業學年度: 101
語文別: 中文
論文頁數: 68
中文關鍵詞: 關聯式資料庫關鍵字查詢查詢拆解條件組合查詢結果摘要
英文關鍵詞: relational database, keyword search, query segmentation, condition combination, result summary
論文種類: 學術論文
相關次數: 點閱:118下載:4
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 當今在網際網路中最普遍的搜尋資訊方式,是使用網路搜尋引擎,給予關鍵字進行查詢。我們希望讓使用者能以接近操作搜尋引擎的查詢方式,給定關鍵字和條件式對於關聯式資料庫內容進行查詢,增加資料庫使用的普及和可用性。本論文之研究目的是對關聯式資料庫提出關鍵字查詢處理技術,能將使用者查詢自動轉換成一個對應的結構化查詢語言的SQL語句,並能符合使用者的搜尋意圖。關鍵字查詢處理技術是將查詢關鍵字進行拆解,拆解成一至多個查詢條件並且分組。接著透過給定設計查詢條件單位以邏輯運算子組合運算的優先順序指定括弧位置,產生最可能表達使用者給予關鍵字查詢的搜尋意圖的條件組合。在決定了查詢條件和邏輯順序組合後,接著轉換成所對應的SQL查詢語句,並且執行於關聯式資料庫。此外,本系統還會依統計觀點分析查詢結果中欄位值的一致性和分佈變化差異進行結果摘要。實驗結果顯示本研究方法之關鍵字查詢處理技術在多數情況下能正確處理單一屬性值、資料型態和屬性值組合、數值條件式的查詢。而所提出的摘要方法也有助於使用者得知隱含在查詢結果的重要資訊。

    By giving keywords to a search engine on Internet is the most popular way of searching information. In order to improve the popularity and availability of relational database, we would like to provide that users can give a query consisting of only keywords and predicates for database to find the required data from the database, which is similar to the way of giving queries on search engines. Accordingly, in this thesis, we propose the query processing techniques for keyword search in relational databases, which can automatically transform a user's keyword query into the corresponding Structured Query Language (SQL) statement according to the query intent of the user implied by the keyword query. The proposed query processing techniques firstly separate the query into multiple predicate units and perform grouping on these units. By defining the priority of query predicates and the combination of logical operations, the parentheses are assigned to the predicates to generate the combination of the predicates which most possibly represents the query intent of the given keyword query. After generating the combination of the predicates, the query is then transformed into the corresponding SQL query and performed on a relational database. Besides, the system can statistically analysis the query results according to the consistency and the distribution of differences on attribute values to provide a summary of the results. The experimental results show that the proposed query processing techniques for keyword search can correctly deal with queries consisting of attribute value, combined with keywords of data types and conditional value expression in most cases. Besides, the provided result summary can help users find the important information which is implicit in the query results.

    附表目錄 iii 附圖目錄 iv 第一章 緒論 1 1.1 研究動機與目的 1 1.2 研究的範圍與限制 2 1.3 論文方法 3 1.4 論文架構 4 第二章 文獻探討 5 2.1 結構性資料之查詢關鍵字處理 5 2.2 候選結果產生及排名技術 10 2.3 搜尋結果彙整分析及呈現方式 12 第三章 系統處理流程 15 第四章 查詢拆解與條件組合 17 4.1 資料庫資料前處理與索引建立 17 4.1.1 資料庫資料前處理 17 4.1.2 索引建立 18 4.2 查詢關鍵字分解 20 4.2.1 查詢字前處理 20 4.2.2 查詢字拆解 22 4.3 條件組合 23 第五章 SQL查詢語句產生與查詢結果摘要 30 5.1 SQL查詢語句產生 30 5.1.1 資料表鍵結關係 30 5.1.2 SQL語句產生 33 5.2 SQL執行結果摘要 35 第六章 實驗結果與討論 41 6.1 實驗資料來源及環境設定 41 6.1.1 實驗資料來源 41 6.1.2 實驗環境 43 6.2 查詢關鍵字轉換成SQL查詢語句正確性評估 44 6.2.1 實驗方法 44 6.2.2實驗結果及分析探討 48 6.3 SQL查詢結果的重要資料摘要效果之評估 58 6.3.1 實驗方法 58 6.3.2 實驗結果及分析探討 59 第七章 結論與未來研究方向 63 7.1 結論 63 7.2 未來研究方向 63 參考文獻 65 附錄A 查詢控制型實驗搜尋意圖描述 68

    [1] B. Aditya, G. Bhalotia, S. Chakrabarti, A. Hulgeri, C. Nakhe, Parag,and S. Sudarshan, “Banks: Browsing and keyword searching in relational databases,” in Proceedings of the 28th international conference on Very Large Data Bases (VLDB), 2002.
    [2] S. Agrawal, S. Chaudhuri, and G. Das, “DBXplorer: A system for keyword-based search over relational databases,” in Proceedings of the 18th International Conference on Data Engineering (ICDE), 2002.
    [3] V. Bicer, T. Tran and R. Nedkov, “Ranking Support for Keyword Search on Structured Data using Relevance Models,” in Proceedings of the 20th ACM international conference on Information and knowledge management (CIKM), 2011.
    [4] A. Chapman, A. Elkiss, M. Jayapandian, Y. Li, A. Nandi and C. Yu, “Making database systems usable,” in Proceedings of ACM international conference on Management of data (SIGMOD), 2007.
    [5] S.Cheng, A.Termehchy and Vagelis Hristidis, “Predicting the Effectiveness of Keyword Queries on Databases,” in Proceedings of the 21st ACM international conference on Information and knowledge management (CIKM), 2012.
    [6] J. Coffman and A. C. Weaver, “A framework for evaluating database keyword search strategies,” in Proceedings of the 19th ACM international conference on Information and knowledge management (CIKM), 2010.
    [7] M. Drosou and E. Pitoura, “ReDRIVE: result-driven database exploration through recommendations,” in Proceedings of the 20th ACM international conference on Information and knowledge management (CIKM), 2011.
    [8] S. Fakhraee and F. Fotouhi, “DBSemSXplorer: Semantic-based Keyword Search System over Relational Databases for Knowledge Discovery,” in Proceedings of the 3rd International Workshop on Keyword Search on Structured Data (KEYS), 2012.
    [9] K.Golenberg, B. Kimelfeld and Y. Sagiv, “Keyword proximity search in complex data graphs,” in Proceedings of ACM international conference on Management of data (SIGMOD), 2008.
    [10] V. Hristidis, L. Gravano, and Y. Papakonstantinou, “Efficient IR-Style keyword search over relational databases,” in Proceedings of the 29th international conference on Very Large Data Bases (VLDB), 2003.
    [11] V. Hristidis and Y. Papakonstantinou, “DISCOVER: Keyword search in relational databases,” in Proceedings of the 28th international conference on Very Large Data Bases (VLDB), 2002.
    [12] Y. Huang , Z. Liu and Y. Chen, “Query biased snippet generation in XML search,” in Proceedings of the 2008 ACM SIGMOD international conference on Management of data (SIGMOD), 2008.
    [13] A. Hulgeri and C. Nakhe, “Keyword Searching and Browsing in Databases using BANKS,” in Proceeding of the 18th International Conference on Data Engineering (ICDE), 2002.
    [14] X. Liu, H. Fang, C. L. Yao and M. Wang, “Finding Relevant Information of Certain Types from Enterprise Data,” in Proceedings of the 20th ACM international conference on Information and knowledge management (CIKM), 2011.
    [15] Z. Liu, P. Sun and Y. Chen, “Structured search result differentiation,” in Proceedings of the VLDB Endowment Volume 2 : 313-324, Aug. 2009.
    [16] Y. Mass and Y. Sagiv, “Language Models for Keyword Search over Data Graphs,” in Proceedings of the fifth ACM international conference on Web search and data mining (WSDM), 2012.
    [17] R. Patil and Z. Chen, “STRUCT: Incorporating Contextual Information for English Query Search on Relational Databases,” in Proceedings of the 3rd International Workshop on Keyword Search on Structured Data (KEYS), 2012.
    [18] J. Pound, A. K. Hudek, I. F. Ilyas and G. Weddell, “Interpreting keyword queries over web knowledge bases,” in Proceedings of the 21st ACM international conference on Information and knowledge management (CIKM), 2012.
    [19] J. X. Yu, L. Qin and L. Chang, “Keyword search in relational databases: A survey,” in in Proceedings of the 26th International Conference on Data Engineering, 2010.
    [20] Z. Zeng, Z. Bao, T. W. Ling and M. L. Lee, “ISearch: An Interpretation based Framework for Keyword Search in Relational Databases,” in Proceedings of the 3rd International Workshop on Keyword Search on Structured Data (KEYS), 2012.
    [21] L.Zhang, Y.Zhang, Y.Chen, “Summarizing Highly Structured Documents for Effective Search Interaction,” in Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval (SIGIR), 2012.

    下載圖示
    QR CODE