Features of web subject-related image and its retrieval significance

Keyword information retrieval is the mainstream way of information retrieval at present. Users need to scan a large amount of text information in the search results to find the information they want, but the process causes inefficiency and poor user experience. In fact, images in the web pages can provide a direct-viewing and fast retrieval way. Through the research on the features of web subject-related image and achieve its automatic identification and extraction, we can display it in the thumbnail together with the page title and summary in the results pages. It can help users filter and browse information in a more convenient way. This paper establishes a web image attribute system from both HTML attributes and external attributes. Then through corresponding automatic extracting algorithms and data analysis it succeeds to gain 16 feature rules of web subject-related image, and finishes building a web subject-related image feature model. The model proves to obtain more than 99% of the extraction rate and filtering rate while applying to the sample data, demonstrating its value in web information retrieval.