A Complex Named Entities Extraction Model Oriented Web Video

Complex named entities can refer to specific objects, literal obvious characteristics, which are closely related entities in our daily life, study and work. Named entity recognition complex cannot form only an important data resources on the Internet to provide a basis for information extraction, but also leverage search engines to help to understand the user´s query intent, which gives targeted, integrated search results. This paper proposes a WEB video proposes a web video oriented model to extract complex named entities. The text around the video-based information (mainly the labels and categories of video information), in accordance with the characteristics of various types of word-class distribution and the between-class distribution, and the complex characteristics of named entities and the relationship between co-occurrence of words, extracted from the various categories of named entity. In our method, a small amount of word is marked for each category. The corpus does not require a large number of marked and prolonged training process, which greatly increases the complexity of the named entity extraction accuracy and efficiency.