System of automatic chinese webpage summarization based on the random walk algorithm of dynamic programming

As the Internet becomes more and more deeply connected with our life, the Internet has brought together mass text material, and it is still in explosive growth. In order to quickly and accurately to help users find the required content, the traditional solution is to use a search engine. However, the results of existing automatic webpage summarization systems for search engine are of low quality. Because they just based on statistical method, gather some sentences in the web document beside the search phrases. Neither symbolizes the subject of the document, nor take into account the user search phrases. According to the shortages, An automatic webpage summarization systems is realized. On the basis of the work done, this paper proposed an automatic text summarization method based on relation graph and text structure analysis. This method firstly segment text into semantic paragraphs. For each semantic paragraph, a subject term discover method based on relation graph analysis is proposed. At last, both search phrase and document subject are take into account, it extracts summary according to the guidance of the subject terms. © Wang et al.