Recommendation system and method based on Internet information

Abstract

According to the recommendation system and method based on the Internet information provided by the invention, by setting the separation weighting module and the weighting reconstruction which are particularly better than those in the prior art, and introducing the central arrangement step based on the first context and the second context, accurate judgment before recall is realized. Meanwhile, unique basic recommendation and recommendation scrambling are introduced, self-adaptive recommendation interference is established for recommendation results, a recommendation page formed by combining the recommendation results is transmitted to a user, and the retrieval, capture and recall technical process of a new generation of retrieved and recommended internet data streams is achieved.

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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