An improved collaborative recommendation algorithm based on optimized user similarity

There are lots of issues existing in traditional collaborative filtering recommendation,.such as data scarcities, cold start, recommendation accuracy and.timeliness. And how to improve the efficiency and quality of recommendation is a.key problem in collaborative recommendation. In the traditional collaborative filtering.algorithms, the rating scale of different users for all projects sometimes may be.neglected while calculating the similarity. Some algorithms such as adjusted cosine.similarity