With the development of the Internet, the amount of information present on the network has grown rapidly, leading to increased difficulty in obtaining effective information. Especially for individuals, enterprises, and institutions with a large amount of information, it is an almost impossible task to integrate and analyze Internet information with great difficulty just by human resources. Internet hot events mining and analysis technology can effectively solve the above problems by alleviating information overload, integrating redundant information, and refining core information. In this paper, we address the above problems and research hot event topic sentence generation techniques in the field of hot event mining and design a hybrid event candidate set construction algorithm based on topic core word mapping and event triad selection. The algorithm uses the PAT-Tree technique to extract high-frequency core words in topic hotspots and maps the high-frequency words into sentences to generate a part of event core sentences. The other part of event core sentences is extracted from the topic hotspots by making event triples as candidate elements, and sentences containing event elements are extracted from the topic hotspots. The sets of event core sentences generated by the two methods are mixed and filtered and sorted to obtain the candidate set, which can be used to build a word graph-based main service channel (MSC) model. In this paper, we also propose an improved word graph-based MSC model and use it for the extraction of event topic sentences. Based on the above research, a hot event analysis system is implemented. The system analyzes the existing topic data and uses the event topic sentence generation algorithm studied in this paper to generate the titles of hot spots, that is, hot events. At the same time, the topics are displayed from different dimensions, and data visualization is completed. The visualization includes the trend change of event hotness, trend change of event sentiment polarity, and distribution of event article sources.

To improve the effect of modern art design, this study presents a camera pose estimation algorithm based on the least feature points of quaternion. Moreover, this study detects and matches the feature points of the camera image and establishes a system of formulas through the rigid constraints of the feature points, thereby constructing an eigenvalue problem to solve the camera pose. In addition, this study combines artificial intelligence technology to construct the modern art interactive design system and structure the system function structure. Finally, this study analyzes the logical structure and spatial structure of the system and uses the design to analyze the performance of the modern art interaction design model proposed in this study. Through experimental research, it can be known that the modern art interactive design system based on artificial intelligence technology proposed in this study can basically meet the artistic design needs of the new media era.