Research on Personalized Search Based on ElasticSearch

In the context of today's big data era, with the rapid development of information technology in all walks of life, information data has exploded. People have been used to relying on the Internet to obtain effective information, but massive data is easy to cause information overload, how to quickly and efficiently obtain useful information for users has become the main problem facing search engines. In order to better study the ElasticSearch application in personalized search, this paper proposes a personalized search engine based on ElasticSearch, on the basis of improve the retrieval efficiency and retrieval accuracy, analysis of user search history records and utilization, let the search engine can be more intelligent, friendlier interact with the user, and makes search results more accord with the actual needs of users. Then, this paper tests and analyzes the search engine in many aspects. The test results show that the search rate has increased by 32.26%, which verifies the practicability, effectiveness and real-time performance of the search engine.