Related resource address push method and device based on video retrieval

Abstract

The invention discloses a related resource address push method and device based on video retrieval. The related resource address push method and device based on the video retrieval comprises the steps of obtaining the characteristic text information of first video resource data when the loading or playing requests of the first video resource data are received, mapping the characteristic text information as one or more first participles, searching related second participles having the co-occurrence rate with the one or more first participles higher than a preset threshold value, wherein the co-occurrence rate is the possibility of the current one or more first participles and the second participles emerge together in identical video resource data, obtaining the network chained addresses of the second video resource data matched with the one or more fist participles and the related second participles, and pushing the network chained addresses of the second video resource data. The related resource address push method and device based on the video retrieval achieves the purpose of delving resources of good quality in a video database deeply, and improves delving efficiency of the resources. In addition, an index table can be enlarged continuously along with the accumulation of the video content of the internet, and the fact that a recall rate is facilitated is enlarged.

Description

technical field [0001] The present invention relates to the technical field of the Internet, in particular to a method for pushing associated resource addresses based on video search and a device for pushing associated resource addresses based on video search. Background technique [0002] Video search engine is a vertical search technology different from comprehensive search. A video search engine crawls and indexes video results on the Internet, and since it can provide pure video results to searchers, it can greatly save Internet users' time in searching for videos. [0003] According to the relevant statistical data of video search, entertainment, games, film and television, news, animation and other types of videos are the main search objects of users. This shows that users have a general demand for video search itself. Users often do not have a strong purpose, and the search results are not "necessary", but have a certain degree of scalability, as long as the target ...

AI Technical Summary

Problems solved by technology

[0004] However, the existing video search engines are not enough in terms of relevant recommendations: some video search engines do not have relevant recommendations, and video search engines with relevant recommendations are only based on the user's search history data, through manual sorting to obtain the correlation system and other simple methods achieve recommendation

For example, when you search for "square dance" on a certain search engine, you will get recommended words such as "ballroom dance", "belly dance", and "aerobics", and when you search for "dota", you will get "Cross Fire", "World of Warcraft", etc. recommended words, but the recall rate of this system is low, and it is generally impossible to give recommendations in long-tail searches

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