The document discusses a new algorithm for topic mining over asynchronous text sequences. The algorithm aims to explore correlations between multiple related text sequences that may have different time stamps. It consists of two alternating steps: 1) extracting common topics from sequences based on adjusted time stamps, and 2) adjusting time stamps according to the discovered topic time distributions. The approach is evaluated on research papers and news articles, demonstrating effectiveness in identifying topics across asynchronously published documents.