Social media retrieval using image features and structured text

被引:0
|
作者
Iskandar, D. N. F. Awang [1 ]
Pehcevski, Jovan [1 ]
Thom, James A. [1 ]
Tahaghoghi, S. M. M. [1 ]
机构
[1] RMIT Univ, Sch Comp Sci & Informat Technol, Melbourne, Vic, Australia
基金
澳大利亚研究理事会;
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
Use of XML offers a structured approach for representing information while maintaining separation of form and content. XML information retrieval is different from standard text retrieval in two aspects: the XML structure may be of interest as part of the query; and the information does not have to be text. In this paper, we describe an investigation of approaches to retrieve text and images from a large collection of XML documents, performed in the course of our participation in the INEX 2006 Ad Hoc and Multimedia tracks. We evaluate three information retrieval similarity measures: Pivoted Cosine, Okapi BM25 and Dirichlet. We show that on the INEX 2006 Ad Hoc queries Okapi BM25 is the most effective among the three similarity measures used for retrieving text only, while Dirichlet is more suitable when retrieving heterogeneous (text and image) data.
引用
下载
收藏
页码:358 / 372
页数:15
相关论文
共 50 条
  • [1] Combining image and structured text retrieval
    Iskandar, D. N. F. Awang
    Pehcevski, Jovan
    Thom, James A.
    Tahaghoghi, S. M. M.
    ADVANCES IN XML INFORMATION RETRIEVAL AND EVALUATION, 2006, 3977 : 525 - 539
  • [2] Geometric discriminative features for aerial image retrieval in social media
    Xia, Yingjie
    Chen, Jinlong
    Li, Jun
    Zhang, Ying
    MULTIMEDIA SYSTEMS, 2016, 22 (04) : 497 - 507
  • [3] Geometric discriminative features for aerial image retrieval in social media
    Yingjie Xia
    Jinlong Chen
    Jun Li
    Ying Zhang
    Multimedia Systems, 2016, 22 : 497 - 507
  • [4] Query expansion by text and image features in image retrieval
    Zhou, H
    Chan, SY
    Kok, FL
    JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 1998, 9 (04) : 287 - 299
  • [5] Text-Image Retrieval With Salient Features
    Feng, Xia
    Hu, Zhiyi
    Liu, Caihua
    Ip, W. H.
    Chen, Huiying
    JOURNAL OF DATABASE MANAGEMENT, 2021, 32 (04) : 1 - 13
  • [6] Combining Image and Text Features for Medicinal Plants Image Retrieval
    Madam, Oki
    Herdiyeni, Yeni
    2013 INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER SCIENCE AND INFORMATION SYSTEMS (ICACSIS), 2013, : 273 - 277
  • [7] Using Text to Teach Image Retrieval
    Dong, Haoyu
    Wang, Ze
    Qiu, Qiang
    Sapiro, Guillermo
    2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2021, 2021, : 1643 - 1652
  • [8] Interactive Image Retrieval Using Text and Image Content
    Dinakaran, B.
    Annapurna, J.
    Kumar, Ch. Aswani
    CYBERNETICS AND INFORMATION TECHNOLOGIES, 2010, 10 (03) : 20 - 30
  • [9] Leveraging Style and Content features for Text Conditioned Image Retrieval
    Chawla, Pranit
    Jandial, Surgan
    Badjatiya, Pinkesh
    Chopra, Ayush
    Sarkar, Mausoom
    Krishnamurthy, Balaji
    2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2021, 2021, : 3973 - 3977
  • [10] FULL TEXT RETRIEVAL FROM STRUCTURED TEXT
    GOLDSTEIN, CM
    BULLETIN OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE, 1989, 15 (06): : 11 - 11