Application Research of Machine Learning Method Based on Distributed Cluster in Information Retrieval

With the rapid development and comprehensive popularization of information technology, in order to reduce resource consumption and environmental pollution, all walks of life have made efforts to promote the construction of information technology in response to the call of the state to achieve paperlessness. When more and more information data is accumulated at the PB level per second, usually we use a kind of information retrieval method to filter the files in the database that quickly and accurately search the data file which users care. This paper proposes a retrieval cluster structure based on distributed network design and performs unsupervised machine learning on the unstructured data content according to the classification learning model, so that the child nodes have the function of automatically identifying the semantics of the article, then the second inverted index is obtained by feedback learning results that it was based on the original index . The practical application results show that the design model is feasible, not only significantly improves the retrieval effect and the accuracy of data screening, but also provides strong support for subsequent big data analysis.