Named entity recognition in crime using machine learning approach

被引:8
|
作者
机构
[1] Shabat, Hafedh
[2] Omar, Nazlia
[3] Rahem, Khmael
来源
Shabat, Hafedh (h2005_ali@yahoo.com) | 1600年 / Springer Verlag卷 / 8870期
关键词
Crime;
D O I
10.1007/978-3-319-12844-3_24
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [41] Named Entity Recognition in Malayalam using Fuzzy Support Vector Machine
    Lakshmi, G.
    Panicker, Janu R.
    Meera, M.
    PROCEEDINGS OF 2016 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE (ICIS), 2016, : 201 - 206
  • [42] Named entity recognition in Bengali and Hindi using support vector machine
    Ekbal, Asif
    Bandyopadhyay, Sivaji
    LINGUISTICAE INVESTIGATIONES, 2011, 34 (01): : 35 - 67
  • [43] FLightNER: A Federated Learning Approach to Lightweight Named-Entity Recognition
    Abadeer, Macarious
    Shi, Wei
    Corriveau, Jean-Pierre
    2022 IEEE INTERNATIONAL CONFERENCE ON TRUST, SECURITY AND PRIVACY IN COMPUTING AND COMMUNICATIONS, TRUSTCOM, 2022, : 687 - 694
  • [44] Pattern acquisition for Chinese named entity recognition: A supervised learning approach
    Fang, XS
    Sheng, HY
    ADVANCES IN INFORMATION SYSTEMS, 2002, 2457 : 166 - 175
  • [45] Named Entity Recognition Using a New Fuzzy Support Vector Machine
    Mansouri, Alireza
    Affendey, Lilly Suriani
    Mamat, Ali
    INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2008, 8 (02): : 320 - 325
  • [46] Active learning approach using a modified least confidence sampling strategy for named entity recognition
    Ankit Agrawal
    Sarsij Tripathi
    Manu Vardhan
    Progress in Artificial Intelligence, 2021, 10 : 113 - 128
  • [47] Active learning approach using a modified least confidence sampling strategy for named entity recognition
    Agrawal, Ankit
    Tripathi, Sarsij
    Vardhan, Manu
    PROGRESS IN ARTIFICIAL INTELLIGENCE, 2021, 10 (02) : 113 - 128
  • [48] Quantitative Analysis of Art Market Using Ontologies, Named Entity Recognition and Machine Learning: A Case Study
    Filipiak, Dominik
    Agt-Rickauer, Henning
    Hentschel, Christian
    Filipowska, Agata
    Sack, Harald
    BUSINESS INFORMATION SYSTEMS (BIS 2016), 2016, 255 : 79 - 90
  • [49] Using machine learning to maintain rule-based named-entity recognition and classification systems
    Petasis, G
    Vichot, F
    Wolinski, F
    Paliouras, G
    Karkaletsis, V
    Spyropoulos, CD
    39TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, PROCEEDINGS OF THE CONFERENCE, 2001, : 418 - 425
  • [50] Named Entity Recognition of Diabetes Online Health Community Data Using Multiple Machine Learning Models
    Xu, Qian
    Zhou, Yue
    Liao, Bolin
    Xin, Zirui
    Xie, Wenzhao
    Hu, Chao
    Luo, Aijing
    BIOENGINEERING-BASEL, 2023, 10 (06):