An Industrial Dyeing Recipe Recommendation System for Textile Fabrics Based on Data-Mining and Modular Architecture Design

Data mining depends on large-scale taxi traces is an important research concepts. A vital direction for analyzing taxi GPS dataset is to suggest cruising areas for taxi drivers. The project first investigates the real-time demand-supply level for taxis, and then makes an adaptive tradeoff between the utilities of drivers and passengers for different hotspots. This project constructs a recommendation system by jointly considering the profits of both drivers and passengers. At last, the qualified candidates are suggested to drivers based on analysis. The project also provides a real-time charging station recommendation system for EV taxis via large-scale GPS data mining. By combining each EV taxi’s historical recharging actions and real-time GPS trajectories, the present operational state of each taxi is predicted. Based on this information, for an EV taxi requesting a recommendation, recommend a charging station that leads to the minimal total time before its recharging starts.

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Traveler's Recommendation System Using Data Mining Techniques

2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA) ◽

10.1109/iccubea.2018.8697862 ◽

2018 ◽

Author(s):

Shrikant Kokate ◽

Ashwini Gaikwad ◽

Pranita Patil ◽

Manisha Gutte ◽

Kalyani Shinde

Keyword(s):

Data Mining ◽

Recommendation System ◽

Data Mining Techniques ◽

Using Data

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Prediction Model on Student Performance based on Internal Assessment using Deep Learning

International Journal of Emerging Technologies in Learning (iJET) ◽

10.3991/ijet.v14i08.10001 ◽

2019 ◽

Vol 14 (08) ◽

pp. 4 ◽

Cited By ~ 3

Author(s):

Sadiq Hussain ◽

Zahraa Fadhil Muhsion ◽

Yass Khudheir Salal ◽

Paraskevi Theodoru ◽

Fikriye Kurtoğlu ◽

...

Keyword(s):

Data Mining ◽

Deep Learning ◽

Student Performance ◽

Recommendation System ◽

Optimization Method ◽

Recognition System ◽

Kappa Statistics ◽

Immune Recognition ◽

Classification Methods ◽

Classification Rate

Educational Data Mining plays a crucial role in identifying academically weak students of an institute and helps to develop different recommendation system for them. Students from three colleges of Assam, India were considered in our research which their records were run on deep learning using sequential neural model and adam optimization method. The paper compared other classification methods such as Artificial Immune Recognition System v2.0 and Adaboost, to find out the prediction of the results of the students. The highest classification rate was 95.34% produced by the deep learning techniques. The Precision, Recall, F-Score, Accuracy, and Kappa Statistics Performance were calculated as a statistics decisions to find the best classification methods. The dataset used in this paper was 10140 student records. Directing the student for their future plan comes from discovering the hidden patterns by using Data Mining techniques.

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A Survey on Data Mining Methods Available for Recommendation System

2017 2nd International Conference on Computational Systems and Information Technology for Sustainable Solution (CSITSS) ◽

10.1109/csitss.2017.8447672 ◽

2017 ◽

Cited By ~ 1

Author(s):

Niranjan Kumar ◽

Y S Sneha ◽

Jitendranath Mungara ◽

S G Raghavendra Prasad

Keyword(s):

Data Mining ◽

Recommendation System ◽

Mining Methods

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Research on Intelligent Recommendation Method and its Application on Internet Bookstore

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.121-122.447 ◽

2010 ◽

Vol 121-122 ◽

pp. 447-452

Author(s):

Qing Zhang Chen ◽

Yu Jie Pei ◽

Yan Jin ◽

Li Yan Zhang

Keyword(s):

Data Mining ◽

Association Rules ◽

Recommendation System ◽

Recommendation Systems ◽

Experimental Results ◽

Personalized Recommendation ◽

The Internet

As the current personalized recommendation systems of Internet bookstore are limited too much in function, this paper build a kind of Internet bookstore recommendation system based on “Strategic Data Mining”, which can provide personalized recommendations that they really want. It helps us to get the weight attribute of type of book by using AHP, the weight attributes spoken on behalf of its owner, and we add it in association rules. Then the method clusters the customer and type of book, and gives some strategies of personalized recommendation. Internet bookstore recommendation system is implemented with ASP.NET in this article. The experimental results indicate that the Internet bookstore recommendation system is feasible.

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