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Author:

He, Jingsha (He, Jingsha.) (Scholars:何泾沙) | Du, Jianghao (Du, Jianghao.) | Zhang, Yixuan (Zhang, Yixuan.) | Zhou, Shiyi (Zhou, Shiyi.)

Indexed by:

EI Scopus

Abstract:

The current Web manifests the problem of information overload due to the success of the Web 2.0 paradigm in which users can provide new contents quickly. To help users find the most valuable information, a recommendation system is designed in which we use Euclidean formula to calculate the distance and Cosine formula to calculate the angle to distinguish between different kinds of users. Thus, similar users will receive related items. In the beginning, we will face some problems such as the cold start due to a small amount of data. We will advance some theories to solve the problem. With the proposed method, we can improve the quality of recommendation so that users can find the most valuable information. © 2014 IEEE.

Keyword:

Recommender systems Computation theory Portals

Author Community:

  • [ 1 ] [He, Jingsha]School of Software Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [He, Jingsha]Low Carbon Research Center, Beijing Development Area Co., Ltd., Beijing; 100176, China
  • [ 3 ] [Du, Jianghao]School of Software Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Zhang, Yixuan]School of Software Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 5 ] [Zhou, Shiyi]Low Carbon Research Center, Beijing Development Area Co., Ltd., Beijing; 100176, China

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Source :

Year: 2014

Page: 70-74

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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