关键词: 维吾尔文, 自动文摘, TF-IDF算法, Textrank, ROUGE

Abstract: As represented by the Internet, development of information technology has enabled people to obtain information easier than ever before, but it also presents challenges to the effective use of information. Automatic summarization techniques greatly improve efficiency in the use of information by automatically selecting representatives of the sentences in the document. In recent years, automatic summarization techniques based on English and Chinese received wide attention and achieved significant progress while the automatic summarization of minority languages is not sufficient, such as Uyghur language. This paper constructs a Uyghur-oriented automatic summarization system. Uyghur linguistic knowledge is used to handle the document, and then keywords which are extracted from the document is used for automatic text summarization. Two different TF-IDF-based and TextRank-based extraction algorithms are compared; it proves TextRank method is more suitable for automatic text summarization. It is demonstrated that on the premise of full account of Uygur language information, automatic text summarization based on keywords can achieve satisfactory results.

Key words: Uyghur, automatic summarization, TF-IDF algorithm, TextRank, ROUGE