A Study on Key Techniques of Wisdom Campus Information Recommendation Platform Based on Big Data

This thesis employs the mainstream Hadoop framework to store and analyze the large-scale data generated in the campus environment. The system will first collect, process and save data by using the HDFS distributed file system. And then data mining and intelligent analysis of the data will be carried out. Last, the recommendation system framework which deals with large dataset will be put forward based on the above two steps. Therefore, a modified collaborative filtering recommendation algorithm based on the students´ similarity will be achieved and the accuracy as well as the efficiency of recommendation will be improved.