T/MSITISA 02-007-2022 Active Group standards

T/MSITISA 02-007-2022 News dissemination service platform news recommendation process and evaluation standards

Publish Date: 2022-05-23 Implement Date: 2022-06-01 For services related to genuine standard inquiry, procurement, translation, and other related services in China, please Contact Us

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Basic Information

Standard Code: T/MSITISA 02-007-2022

Standard Type: Group standards

Standard Status: Active

is_force_gb: no

CCS Name: -

ICS Name: Comprehensive Application of Information Technology

Publish Date: 2022-05-23

Implement Date: 2022-06-01

Scope

Main technical content: With the rapid development of interactive communication technology, news dissemination service platforms have become an important source of news media due to their strong availability and real-time information updating features. However, with the increase in user base and the rapid expansion of news volume, the problem of information overload has become particularly prominent. Personalized news recommendation technology is an effective way to alleviate news information overload, which can help users screen and push news that may interest them from numerous news resources. It is currently a hot research topic in both academia and industry. However, there are currently no unified standards and norms for the news recommendation process and evaluation of news dissemination service platforms, which has affected the further application and promotion of news recommendation. To solve this problem, Beijing University of Posts and Telecommunications and other units, based on theoretical research, combined with typical service scenarios to carry out application demonstrations, standardized the specific process of news recommendation, established unified recommendation standards, and promoted the standardized development of the news recommendation field. This document unifies and standardizes the recommendation process and evaluation indicators of news recommendation platforms through stipulating the recommendation process and evaluation indicators. This document mainly includes two parts: the news recommendation process and the news recommendation evaluation indicators.