Cross-media Scientific Research Achievements Query based on Ranking Learning
For scientific researchers and managers, this work addresses the need for better cross-media query of scientific achievements, but it is an incremental survey without experimental validation.
The paper addresses the challenge of querying cross-media scientific research achievements (text, images, videos) with proper nouns and ambiguity, proposing a ranking learning-based approach. No concrete results or numbers are provided.
With the advent of the information age, the scale of data on the Internet is getting larger and larger, and it is full of text, images, videos, and other information. Different from social media data and news data, scientific research achievement information has the characteristics of many proper nouns and strong ambiguity. The traditional single-mode query method based on keywords can no longer meet the needs of scientific researchers and managers of the Ministry of Science and Technology. Scientific research project information and scientific research scholar information contain a large amount of valuable scientific research achievement information. Evaluating the output capability of scientific research projects and scientific research teams can effectively assist managers in decision-making. In view of the above background, this paper expounds on the research status from four aspects: characteristic learning of scientific research results, cross-media research results query, ranking learning of scientific research results, and cross-media scientific research achievement query systems.