MOFSRank: A Multiobjective Evolutionary Algorithm for Feature Selection in Learning to Rank
المؤلفون المشاركون
Zhang, Xingyi
Cheng, Fan
Guo, Wei
المصدر
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-14، 14ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-12-02
دولة النشر
مصر
عدد الصفحات
14
التخصصات الرئيسية
الملخص EN
Learning to rank has attracted increasing interest in the past decade, due to its wide applications in the areas like document retrieval and collaborative filtering.
Feature selection for learning to rank is to select a small number of features from the original large set of features which can ensure a high ranking accuracy, since in many real ranking applications many features are redundant or even irrelevant.
To this end, in this paper, a multiobjective evolutionary algorithm, termed MOFSRank, is proposed for feature selection in learning to rank which consists of three components.
First, an instance selection strategy is suggested to choose the informative instances from the ranking training set, by which the redundant data is removed and the training efficiency is enhanced.
Then on the selected instance subsets, a multiobjective feature selection algorithm with an adaptive mutation is developed, where good feature subsets are obtained by selecting the features with high ranking accuracy and low redundancy.
Finally, an ensemble strategy is also designed in MOFSRank, which utilizes these obtained feature subsets to produce a set of better features.
Experimental results on benchmark data sets confirm the advantage of the proposed method in comparison with the state-of-the-arts.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Cheng, Fan& Guo, Wei& Zhang, Xingyi. 2018. MOFSRank: A Multiobjective Evolutionary Algorithm for Feature Selection in Learning to Rank. Complexity،Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1135938
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Cheng, Fan…[et al.]. MOFSRank: A Multiobjective Evolutionary Algorithm for Feature Selection in Learning to Rank. Complexity No. 2018 (2018), pp.1-14.
https://search.emarefa.net/detail/BIM-1135938
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Cheng, Fan& Guo, Wei& Zhang, Xingyi. MOFSRank: A Multiobjective Evolutionary Algorithm for Feature Selection in Learning to Rank. Complexity. 2018. Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1135938
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1135938
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