دانلود رایگان مقاله انگلیسی سیستم ثبت سفارش هوشمند لباس مبتنی بر سیستم خبره - اشپرینگر 2018

عنوان فارسی
سیستم ثبت سفارش هوشمند لباس مبتنی بر سیستم خبره
عنوان انگلیسی
Intelligent Costume Recommendation System Based on Expert System
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
8
سال انتشار
2018
نشریه
اشپرینگر - Springer
فرمت مقاله انگلیسی
PDF
نوع مقاله
ISI
پایگاه
اسکوپوس
کد محصول
E10400
رشته های مرتبط با این مقاله
مهندسی کامپیوتر، فناوری اطلاعات
گرایش های مرتبط با این مقاله
هوش مصنوعی، سامانه های شبکه ای
مجله
مجله دانشگاه جیائو تونگ شانگهای - علوم - Journal of Shanghai Jiaotong University - Science
دانشگاه
College of Information Science and Technology - Donghua University - Shanghai - China
کلمات کلیدی
سفارش لباس، سیستم کارشناس، مدل تخته سیاه، اضافه کردن فهرست
doi یا شناسه دیجیتال
https://doi.org/10.1007/s12204-018-1933-x
چکیده

Abstract: On the basis of expert system, we design a costume recommendation system which provides customers with clothing collocation solution and more experience. We set up a costume matching knowledge base collected from experts, and represent the knowledge with production rules. By analyzing the customers’ specific physical information got through man-machine interface, the proposed system provides customers an intelligent costume recommendation strategy in accordance with blackboard model reasoning. Moreover, index adding algorithm is integrated into the traditional serial blackboard model in the system. Finally, we present experiments which show the search rate is improved significantly.

نتیجه گیری

Conclusion


The costume recommendation system based on expert system designed in this paper aims to solve the subjective shortcomings of artificial clothing recommendation systems. The knowledge base in the proposed system stores the recommendation rules in the form of production rules, and the inference engine focuses on the blackboard model. This paper also proposes an optimization method of index adding to fasten the search speed of the recommendation result. Experimental implementation of the proposed system, using the data collected from the volunteers and the open websites, shows that the recommendation efficiency of the model is improved. One further direction is to update the knowledge base with intelligent acquisition method, and the customers’ information in the system can also be broadened to the occupation, age, suitable occasions and so on.


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