Research on Search Engine of Knowledge Adaptation System Based on Large Scale Data Set

The world has entered the era of knowledge economy, knowledge is becoming the core of social production. Any organization or individual can only continue to strengthen the application of knowledge, in today's changeable, fast changing, change in the competition to stand out. Provides a rich source of data explosion of information and knowledge for knowledge application, knowledge management research direction of past and existing knowledge, needs the shortcomings, which introduced the large-scale data adapter based on knowledge. Large data sets in the memory not only need to consume a large amount of storage space, but also put forward higher requirements for data retrieval, and the existing search engine is not very good to meet the needs of knowledge adaptation system. Based on large data sets, this paper mainly studies the retrieval system of knowledge adaptation system. The selection of the algorithm for the search engine, the analysis of the deficiencies, and put forward a targeted improvement program-kNN algorithm to increase the pre process, expand the scope of application and effect of the engine. Finally, the efficiency and effectiveness of the model are verified by the example of forest cover.