C Language Teaching Platform Design Based on Blockly Open-Source Software

Given the massive and complex nature of new media advertising information, users need to effectively search and filter relevant advertisements. This paper proposes a multifunctional search optimization scheme for new media advertising information based on XML technology. This scheme first integrates user attribute data, constructs membership functions and deterministic index systems to accurately characterize the comprehensive attributes of advertisements and classify them. By calculating the average value of constant threshold elements, a model of the attractiveness of advertisements to users is established to quantify the similarity between text information and queries, as well as user browsing behavior. On this basis, design a search model to sort and merge advertising information, generating accurate search results. Experiments have shown that dynamic new media advertisements are more attractive than static types, and this method significantly improves search efficiency to over 90%, while ensuring a high level of 98% match between search content and keywords.