WebTheme™:: Understanding Web information through visual analytics

被引:0
|
作者
Whiting, MA [1 ]
Cramer, N [1 ]
机构
[1] Pacific NW Natl Lab, Richland, WA 99352 USA
来源
SEMANTIC WEB - ISWC 2002 | 2002年 / 2342卷
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
WebTheme combines the power of software agent-based information retrieval with visual analytics to provide users with a new tool for understanding web information. WebTheme allows users to both quickly comprehend large collections of information from the Web and drill down into interesting portions of a collection. Software agents work for users to perform controlled harvesting of web material of interest. Visualization and analysis tools allow exploration of the resulting document space. Information spaces are organized and presented according to their topical context. Tools that display how documents were collected by the agents, where they were gathered, and how they are linked further enhance users' understanding of information and its context. WebTheme is a significant tool in the pursuit of the Semantic Web. In particular, it supports enhanced user insight into semantics of large, prestructured or ad-hoc, web information collections.
引用
收藏
页码:460 / 468
页数:9
相关论文
共 50 条
  • [41] Flight web searches analytics through big data
    Khalil, Amna
    Awan, Mazhar Javed
    Yasin, Awais
    Singh, Vishwa Pratap
    Shehzad, Hafiz Muhammad Faisal
    INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY, 2022, 68 (03) : 260 - 268
  • [42] Library Sites as Seen through the Lens of Web Analytics
    N. S. Redkina
    Redkina, N.S. (redkina@gpntbsib.ru), 2018, Pleiades journals (52) : 91 - 96
  • [43] Understanding of the predictability and uncertainty in population distributions empowered by visual analytics
    Luo, Peng
    Chen, Chuan
    Gao, Song
    Zhang, Xianfeng
    Chol, Deng Majok
    Yang, Zhuo
    Meng, Liqiu
    INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, 2025, 39 (03) : 675 - 705
  • [44] SANVis: Visual Analytics for Understanding Self-Attention Networks
    Park, Cheonbok
    Na, Inyoup
    Jo, Yongjang
    Shin, Sungbok
    Yoo, Jaehyo
    Kwon, Bum Chul
    Zhao, Jian
    Noh, Hyungjong
    Lee, Yeonsoo
    Choo, Jaegul
    2019 IEEE VISUALIZATION CONFERENCE (VIS), 2019, : 146 - 150
  • [45] Towards the Characterization of Individual Users through Web Analytics
    Goncalves, Bruno
    Ramasco, Jose J.
    COMPLEX SCIENCES, PT 2, 2009, 5 : 2247 - +
  • [46] Understanding and Information in the Work of Visual Artists
    Gorichanaz, Tim
    JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY, 2020, 71 (06) : 685 - 695
  • [47] Roses Have Thorns: Understanding the Downside of Oncological Care Delivery Through Visual Analytics and Sequential Rule Mining
    Floricel, Carla
    Wentzel, Andrew
    Mohamed, Abdallah
    Fuller, C. David
    Canahuate, Guadalupe
    Marai, G. Elisabeta
    IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2024, 30 (01) : 1227 - 1237
  • [48] Providing visual analytics guidance through decision support
    Han, Wenkai
    Schulz, Hans-Jorg
    INFORMATION VISUALIZATION, 2023, 22 (02) : 140 - 165
  • [49] Augmenting Digital Sheet Music through Visual Analytics
    Miller, Matthias
    Fuerst, Daniel
    Hauptmann, Hanna
    Keim, Daniel A.
    El-Assady, Mennatallah
    COMPUTER GRAPHICS FORUM, 2022, 41 (01) : 301 - 316
  • [50] Detecting Criminal Relationships Through SOM Visual Analytics
    Wang, Wen Bo
    Huang, Mao Lin
    Zhang, Jinson
    Lai, Wei
    2015 19TH INTERNATIONAL CONFERENCE ON INFORMATION VISUALISATION IV 2015, 2015, : 316 - 321