Research on Intellectual Property Retrieval based on intelligent recommendation algorithm

DOI

10.2991/978-94-6463-264-4_13How to use a DOI?

Keywords

Recommendation algorithm; Intellectual property rights; Literature retrieval

Abstract

Effective retrieval of intellectual property is of great significance for promoting innovation and protecting intellectual property rights and interests. Aiming at the problems of information overload and low accuracy existing in traditional retrieval methods of intellectual property, this paper proposes an innovative intellectual property model based on recommendation algorithm, aiming at exploring intellectual property retrieval methods based on intelligent recommendation algorithm. To improve the retrieval efficiency and accuracy. The process mainly includes: data preprocessing, feature extraction and recommendation model construction. Firstly, the intelligent recommendation algorithm is summarized and the application potential of intelligent recommendation algorithm in intellectual property retrieval is analyzed. Then it introduces the key problems in intellectual property retrieval, including keyword extraction, document representation and similarity calculation. Then, the intellectual property retrieval model based on intelligent recommendation algorithm is elaborated. Finally, the performance of intellectual property retrieval method based on intelligent recommendation algorithm is verified by experiments, and compared with the traditional method. The experimental results show that the intellectual property retrieval method based on intelligent recommendation algorithm has high retrieval efficiency and accuracy, can provide personalized intellectual property information recommendation service, and provide strong support for the protection and application of intellectual property.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Dianyong Yu
AU  - Yunliang Sun
AU  - Vadzim Samaryn
PY  - 2023
DA  - 2023/09/28
TI  - Research on Intellectual Property Retrieval based on intelligent recommendation algorithm
BT  - Proceedings of the 2023 3rd International Conference on Education, Information Management and Service Science (EIMSS 2023)
PB  - Atlantis Press
SP  - 112
EP  - 119
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-264-4_13
DO  - 10.2991/978-94-6463-264-4_13
ID  - Yu2023
ER  -