The article presents a method for summarizing a single document by using information from other documents on the same topic. By combining topic information from related documents and statistical data from the target document, the method assigns scores to sentences. These scores are then used to rank sentences in the target document. The final summary is generated using a biased random walk algorithm and the Maximal Marginal Relevance (MMR) algorithm. The results from experiments on specific datasets show that incorporating information from related documents improves the effectiveness of the summary extraction process.