A recommendation system and method based on Internet information

Abstract

The present invention proposes a recommendation system and method based on Internet information. By setting a separate weighting module and weighting structure that are better than the prior art, and introducing a centering step based on the first and second contexts, the recall before accurate judgment. At the same time, the unique basic recommendation and recommendation scrambling are introduced, and the appeal is to establish adaptive recommendation interference for the recommendation results and deliver the recommended page composed of the current recommendation results to the user, so as to realize the new generation of Internet data stream retrieval, capture and retrieval from retrieval to recommendation. Recall technical process.

Description

technical field [0001] The invention belongs to the field of new generation computer information technology, and in particular relates to a recommendation system and method for Internet information. Background technique [0002] In the era of big data, there are so many types of Internet information that it is difficult to count. Effective information retrieval and recommendation through the Internet has become an important process for the application of network technology and the localization and industrialization of Internet information. For example, by retrieving useful Internet information Guide IT, finance, road and bridge construction, municipal administration and other industries. [0003] Using search to anchor Internet information and viewing recommended content based on search results is an information recommendation method that is more easily accepted by users. [0004] A complete search engine often contains more complex modules, and each module interacts and ma...

AI Technical Summary

Problems solved by technology

[0011] The Internet information recommendation in the prior art does not consider the auxiliary elements in the page content, and the recommendation and retrieval process is implemented in a single line, the logic is relatively simple, and the comparison, synthesis and weight distribution of multi-entry parameters have not been fully realized, and there is no information about the user's own information. Adapting to the context analysis of the recall results, the current Internet information recommendation method has high complexity, but at the same time, the recall results are not good, user satisfaction is low, and there are many repeated recommendations and recommendation deviations

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