Here is my situation. I have a corpus of over 500,000 news. Now I need to cluster the news based on closeness in time and cosine similarity, using vector-space model and TF-IDF weights. I want to cluster the news that report the same event. Clustering performance is beyond time efficiency.
I think about using a slide window, only clustering news "week per unit"(making an assumption that one event is reported within a week).
Any ideas for this problem? Looking forward for the a suggestions:) Thanks in advance.