Research on web text clustering based on DBSCAN optimization algorithm

Zhiwei Liu; Yan Yang

doi:10.1117/12.2654572

20 October 2022 Research on web text clustering based on DBSCAN optimization algorithm

Zhiwei Liu, Yan Yang

Proceedings Volume 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022); 1235026 (2022) https://doi.org/10.1117/12.2654572
Event: 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 2022, Qingdao, China

Abstract

As the amount of information on the Web continues to expand, the way people access information has also changed. Instead of searching for information in paper books or libraries, people are now searching for relevant information on the Web. However, the amount of data on the Web is so large that it is almost impossible to construct an effective data warehouse to replicate, store and integrate all the data on the Web, and there is neither a unified category code nor an effective organisation of indexing in such a large collection of data, which makes content management and information filtering on the Web increasingly difficult and important. In traditional Web applications there are a large number of redundant words, syntax and other problems that make it impossible to use computers to extract useful information accurately and efficiently, so how to effectively use the available resources is one of the urgent and pressing issues that need to be addressed. Therefore, this paper explores Web text clustering based on the DBSCAN optimization algorithm.

Citation Download Citation

Zhiwei Liu and Yan Yang "Research on web text clustering based on DBSCAN optimization algorithm", Proc. SPIE 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 1235026 (20 October 2022); https://doi.org/10.1117/12.2654572

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