Localized Ambient Solidity Separation Algorithm Based Computer User Segmentation
المؤلفون المشاركون
Sun, Xiao
Zhang, Tongda
Chai, Yueting
Liu, Yi
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-16، 16ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-06-28
دولة النشر
مصر
عدد الصفحات
16
التخصصات الرئيسية
الملخص EN
Most of popular clustering methods typically have some strong assumptions of the dataset.
For example, the k -means implicitly assumes that all clusters come from spherical Gaussian distributions which have different means but the same covariance.
However, when dealing with datasets that have diverse distribution shapes or high dimensionality, these assumptions might not be valid anymore.
In order to overcome this weakness, we proposed a new clustering algorithm named localized ambient solidity separation (LASS) algorithm, using a new isolation criterion called centroid distance.
Compared with other density based isolation criteria, our proposed centroid distance isolation criterion addresses the problem caused by high dimensionality and varying density.
The experiment on a designed two-dimensional benchmark dataset shows that our proposed LASS algorithm not only inherits the advantage of the original dissimilarity increments clustering method to separate naturally isolated clusters but also can identify the clusters which are adjacent, overlapping, and under background noise.
Finally, we compared our LASS algorithm with the dissimilarity increments clustering method on a massive computer user dataset with over two million records that contains demographic and behaviors information.
The results show that LASS algorithm works extremely well on this computer user dataset and can gain more knowledge from it.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Sun, Xiao& Zhang, Tongda& Chai, Yueting& Liu, Yi. 2015. Localized Ambient Solidity Separation Algorithm Based Computer User Segmentation. Computational Intelligence and Neuroscience،Vol. 2015, no. 2015, pp.1-16.
https://search.emarefa.net/detail/BIM-1057765
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Sun, Xiao…[et al.]. Localized Ambient Solidity Separation Algorithm Based Computer User Segmentation. Computational Intelligence and Neuroscience No. 2015 (2015), pp.1-16.
https://search.emarefa.net/detail/BIM-1057765
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Sun, Xiao& Zhang, Tongda& Chai, Yueting& Liu, Yi. Localized Ambient Solidity Separation Algorithm Based Computer User Segmentation. Computational Intelligence and Neuroscience. 2015. Vol. 2015, no. 2015, pp.1-16.
https://search.emarefa.net/detail/BIM-1057765
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1057765
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر