A Film and TV News Digest Generation method Based on HanLP
Qing Wu, Qingsheng Li, Jingjing Zhou, XiaoYa Long, Yunqing Guan, HongPing Lin · 2020
Recent years have seen a rapid development of film and television industry, Concurrent with this increase has been a steady rise in user demands on the quality of video content on Internet. This paper mainly introduces HanLP natural language processing package and TextRank algorithm, explains its operation principle in detail by comparing PageRank and TextRank, so as to further study the automatic abstract generation technology of entertainment film and television news. Based on the natural language processing toolkit HanLP, this paper improves and strengthens the abstract generation technique and realizes the core sentence generation. We conduct comprehensive experimental studies. The experimental results show that this method used in this study is of higher quality and more readable than state-of-the-art methods. This technology can also effectively analyze important sentences in film and television news, generate readable abstracts, provide convenience for readers to extract the core fragments of the text, and has certain application value.