Research on Personalized Recommendation of Magnetic Material Retrieval Based on Knowledge Mapping

DOI

10.2991/pntim-19.2019.6How to use a DOI?

Keywords

Magnetic Material; Knowledge Map; Personalized Recommendation

Abstract

Since the concept of knowledge map was introduced, the internet has gradually changed from hyperlink between web pages to describing the association between entities.Knowledge map is mainly used in personalized recommendation and other fields. It can provide users with knowledge nodes and links between nodes.In order to make personalized recommendation for each user's interests and hobbies, based on magnetic material knowledge map and collaborative filtering algorithm, this paper uses python language to mine the interests and hobbies of potential customers. through mining, summarizing, sorting and in-depth analysis of user data, combining the weight of time data and the weight of information similarity, this paper constructs the knowledge map architecture of magnetic material products, realizes the application of process and recommendation algorithm, and proposes the personalized recommendation system architecture of magnetic material retrieval based on knowledge map, which provides a technical scheme for the establishment of personalized learning resource recommendation system.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Li Lei
AU  - Bai Yu
PY  - 2019/11
DA  - 2019/11
TI  - Research on Personalized Recommendation of Magnetic Material Retrieval Based on Knowledge Mapping
BT  - Proceedings of the 2019 International Conference on Precision Machining, Non-Traditional Machining and Intelligent Manufacturing (PNTIM 2019)
PB  - Atlantis Press
SP  - 23
EP  - 26
SN  - 2589-4943
UR  - https://doi.org/10.2991/pntim-19.2019.6
DO  - 10.2991/pntim-19.2019.6
ID  - Lei2019/11
ER  -