Structural feedback for keyword-based XML retrieval

被引:0
|
作者
Schenkel, Ralf [1 ]
Theobald, Martin [1 ]
机构
[1] Max Planck Inst Informat, Saarbrucken, Germany
来源
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Keyword-based queries are an important means to retrieve information from XML collections with unknown or complex schemas. Relevance Feedback integrates relevance information provided by a user to enhance retrieval quality. For keyword-based XML queries, feedback engines usually generate an expanded keyword query from the content of elements marked as relevant or nonrelevant. This approach that is inspired by text-based IR completely ignores the semistructured nature of XML. This paper makes the important step from pure content-based to structural feedback. It presents a framework that expands a keyword query into a full-fledged content-and-structure query. Extensive experiments with the established INEX benchmark and our TopX search engine show the feasibility of our approach.
引用
收藏
页码:326 / 337
页数:12
相关论文
共 50 条
  • [1] An effective and efficient approach for keyword-based XML retrieval
    Li, XG
    Gong, H
    Wang, DL
    Yu, G
    [J]. ADVANCES IN WEB-AGE INFORMATION MANAGEMENT, PROCEEDINGS, 2005, 3739 : 56 - 67
  • [2] Keyword-based Vehicle Retrieval
    Park, Eun-Ju
    Kim, Hoyoung
    Jeong, Seonghwan
    Kang, Byungkon
    Kwon, YoungMin
    [J]. 2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2021, 2021, : 4215 - 4222
  • [3] Keyword-based information retrieval for the WoT
    Xylomenos, George
    Zafeiratos, Evangelos
    Prokopakis, Marios
    [J]. Proceedings of the 4th ACM/IEEE Symposium on Edge Computing, SEC 2019, 2019, : 407 - 412
  • [4] KEMB: A Keyword-Based XML Message Broker
    Li, Guoliang
    Feng, Jianhua
    Wang, Jianyong
    Zhou, Lizhu
    [J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2011, 23 (07) : 1035 - 1049
  • [5] Keyword-based information retrieval for the WoT
    Xylomenos, George
    Zafeiratos, Evangelos
    Prokopakis, Marios
    [J]. SEC'19: PROCEEDINGS OF THE 4TH ACM/IEEE SYMPOSIUM ON EDGE COMPUTING, 2019, : 407 - 412
  • [6] XObject: An XML keyword search method based on structural retrieval
    Li, Xia
    Li, Zhanhuai
    Chen, Qun
    Wang, Peng
    Lou, Ying
    [J]. Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University, 2010, 28 (04): : 602 - 608
  • [7] Automatic medical image annotation and keyword-based image retrieval using relevance feedback
    Ko, Byoung Chul
    Lee, JiHyeon
    Nam, Jae-Yeal
    [J]. JOURNAL OF DIGITAL IMAGING, 2012, 25 (04) : 454 - 465
  • [8] Automatic medical image annotation and keyword-based image retrieval using relevance feedback
    Byoung Chul Ko
    JiHyeon Lee
    Jae-Yeal Nam
    [J]. Journal of Digital Imaging, 2012, 25 : 454 - 465
  • [9] Efficient Declustering Techniques for keyword-based Information Retrieval
    Behl, S
    Verma, RM
    [J]. PARALLEL AND DISTRIBUTED COMPUTING SYSTEMS, 2002, : 294 - 300
  • [10] LAF: a new XML encoding and indexing strategy for keyword-based XML search
    Deng, Zhi-Hong
    Xiang, Yong-Qing
    Gao, Ning
    [J]. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2013, 25 (11): : 1604 - 1621