Exclusive Item Partition with Fuzziness Tuning in MMMs-Induced Fuzzy Co-clustering

被引：0
|
作者：
Nakano, Takaya [1 ]
Honda, Katsuhiro [1 ]
Ubukata, Seiki [1 ]
Notsu, Akira [1 ]
机构：
[1] Osaka Prefecture Univ, Sakai, Osaka 5998531, Japan
来源：
INTEGRATED UNCERTAINTY IN KNOWLEDGE MODELLING AND DECISION MAKING, IUKM 2016 | 2016年 / 9978卷
关键词：
Fuzzy clustering; Co-clustering; Exclusive partition;
D O I：
10.1007/978-3-319-49046-5_16
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Fuzzy co-clustering achieves dual partition of object-item pairs by estimating fuzzy memberships of them. In the multinomial mixtures-induced model, object memberships present the exclusive assignment to clusters while item memberships describe relative typicality in each cluster. In order to improve the interpretability of item partition, exclusive penalty was adopted for item memberships in previous works, where item fuzzy memberships are estimated reflecting both fuzzification penalty and exclusive penalty. In this paper, the characteristics of exclusive item penalty are further studied considering the influences of the item fuzziness weight with different fuzziness degrees.
引用
收藏
页码：185 / 194
页数：10
相关论文
共 50 条
  • [1] MMMs-Induced Fuzzy Co-clustering with Exclusive Partition Penalty on Selected Items
    Nakano, Takaya
    Honda, Katsuhiro
    Ubukata, Seiki
    Notsu, Akira
    [J]. INTEGRATED UNCERTAINTY IN KNOWLEDGE MODELLING AND DECISION MAKING, IUKM 2015, 2015, 9376 : 226 - 235
  • [2] A Heuristic-Based Model for MMMs-Induced Fuzzy Co-Clustering with Dual Exclusive Partition
    Honda, Katsuhiro
    Hakui, Yoshiki
    Ubukata, Seiki
    Notsu, Akira
    [J]. JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS, 2020, 24 (01) : 40 - 47
  • [3] A Deterministic Clustering Framework in MMMs-Induced Fuzzy Co-clustering
    Oshio, Shunnya
    Honda, Katsuhiro
    Ubukata, Seiki
    Notsu, Akira
    [J]. INTEGRATED UNCERTAINTY IN KNOWLEDGE MODELLING AND DECISION MAKING, IUKM 2015, 2015, 9376 : 204 - 213
  • [4] A Noise Fuzzy Co-clustering Scheme in MMMs-induced Clustering
    Honda, Katsuhiro
    Yamamoto, Nami
    Ubukata, Seiki
    Notsu, Akira
    [J]. 2016 JOINT 8TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS (SCIS) AND 17TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS (ISIS), 2016, : 695 - 699
  • [5] MMMs-Induced Possibilistic Fuzzy Co-Clustering and its Characteristics
    Ubukata, Seiki
    Koike, Katsuya
    Notsu, Akira
    Honda, Katsuhiro
    [J]. JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS, 2018, 22 (05) : 747 - 758
  • [6] Deterministic Annealing Framework in MMMs-Induced Fuzzy Co-Clustering and Its Applicability
    Oshio, Shunnya
    Honda, Katsuhiro
    Ubukata, Seiki
    Notsu, Akira
    [J]. INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2016, 16 (01): : 43 - 50
  • [7] A Semi-Supervised Framework for MMMs-Induced Fuzzy Co-Clustering with Virtual Samples
    Tanaka, Daiji
    Honda, Katsuhiro
    Ubukata, Seiki
    Notsu, Akira
    [J]. ADVANCES IN FUZZY SYSTEMS, 2016, 2016
  • [8] A Study on Partition Quality of Fuzzy Co-clustering with Exclusive Item Memberships
    Honda, Katsuhiro
    Nakano, Takaya
    Ubukata, Seiki
    Notsu, Akira
    [J]. 2015 4TH INTERNATIONAL CONFERENCE ON INFORMATICS, ELECTRONICS & VISION ICIEV 15, 2015,
  • [9] Basic Consideration of Online and Mini-Batch Algorithms for MMMs-induced Fuzzy Co-clustering
    Ubukata, Seiki
    Kida, Keiko
    Notsu, Akira
    Honda, Katsuhiro
    [J]. 2018 INTERNATIONAL CONFERENCE ON FUZZY THEORY AND ITS APPLICATIONS (IFUZZY), 2018, : 85 - 90
  • [10] A Study on Recommendation Ability in Collaborative Filering by Fuzzy Co-clustering with Exclusive Item Partition
    Nakano, Takaya
    Honda, Katsuhiro
    Ubukata, Seiki
    Notsu, Akira.
    [J]. 2016 JOINT 8TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS (SCIS) AND 17TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS (ISIS), 2016, : 686 - 689
12345