Intelligent search recommendation method for content, storage medium and terminal

Abstract

The invention relates to a content intelligent search recommendation method, a storage medium and a terminal. The method comprises the steps of matching a document title with keywords extracted from document content, and combining the matched keywords into core keywords according to the matching sequence of the keywords and words in the document title; storing the core keyword and the corresponding relation between the core keyword and the document; receiving a retrieval keyword, and searching a retrieval result corresponding to the retrieval keyword; selecting a part of retrieval result according to the page structure of the display page to display; And carrying out hidden display on the unselected retrieval result, and taking the unselected retrieval result as information required by search engine optimization. According to the invention, a service closed loop in the vertical field is broken through for a single content; and the scheme is a recommendation idea of multiplexing searchlogic, so that the scheme has the advantages of low development cost, high reusability, flexibility and easiness in expansion, and the recommended display comprises dominant display and implicit display, so that the information display amount is richer, the user experience is not influenced, and the SEO of the search engine is facilitated.

Description

technical field [0001] The invention relates to the field of searching for electronic components, and more specifically, relates to an intelligent search and recommendation method for content, a storage medium and a terminal. Background technique [0002] In the field of retrieval of electronic components and supporting materials of electronic components, prior art retrieval uses manual extraction of core points or extraction of core points based on the frequency of captured words at the stage of database establishment. Using manual extraction of core points leads to high cost and low efficiency, and cannot Meet the processing requirements of large amounts of data. Extracting the core points based on the frequency of captured words can only reflect the number of times the word appears in the document, and cannot know whether it is the core meaning of the document from the meaning, which leads to inaccurate search results later. Contents of the invention [0003] The techn...

AI Technical Summary

Problems solved by technology

[0002] In the field of retrieval of electronic components and supporting materials of electronic components, prior art retrieval uses manual extraction of core points or extraction of core points based on the frequency of captured words at the stage of database establishment. Using manual extraction of core points leads to high cost and low efficiency, and cannot Meet the processing requirements of large amounts of data

Extracting the core points based on the frequency of captured words can only reflect the number of times the word appears in the document, and cannot tell whether it is the core meaning of the document from the meaning, resulting in inaccurate search results later

Images