Vertical search method and system for video websites

Abstract

The invention discloses a vertical search method and system for video websites. The method comprises the steps of obtaining data sources of video data with various dimensions, converting the data sources into data models established according to a predetermined data structure, storing the data models as materialized view files, establishing reverse index files of the video data according to the data sources, obtaining reverse index result sets of the video data from the reverse index files according to received retrieval information, and sorting the reverse index result sets according to selected sorting parameters. According to the vertical search method and system for the video websites, vertical search for video resources is achieved, and the retrieval efficiency of the video resources is effectively improved.

Description

technical field [0001] The invention relates to information retrieval technology, in particular to a vertical search method and system for a video website. Background technique [0002] With the development of science and technology, more and more users search and watch various videos through the Internet. Because the video information provided by the Internet is very rich, and has the characteristics of constant change and update, a variety of search engines have emerged for video information retrieval. [0003] In relational database systems, indexes are the most efficient way to retrieve data. But for the video search engine of the whole network, it cannot meet its special requirements. Because search engines are faced with massive video data on the entire network, such as LeTV and other large-scale video websites, the search engine indexes have hundreds of millions or even hundreds of billions of webpages. Facing such a large amount of video data, it is difficult for t...

AI Technical Summary

Problems solved by technology

But for the video search engine of the whole network, it cannot meet its special requirements

Because search engines are faced with massive video data on the entire network, such as LeTV and other large-scale video websites, the search engine indexes have hundreds of millions or even hundreds of billions of webpages. Facing such a large amount of video data, it is difficult for the database system to effective management

[0004] When searching the whole network, a large number of retrieval results will be generated, but the useful information needed by users cannot be quickly found, and cannot meet the sorting requirements

[0005] To sum up, it can be seen that the vertical search of massive video resources in the prior art has not yet proposed an effective solution, so it is necessary to propose improved technical means to solve the above problems

Images