Abstract
In the process of developing major sports events, how to guide providers and users to provide and utilize the archives information resources of major sports events and realize the interaction between them is an important problem to be solved urgently in the development of major sports events and the archive service of major sports events. By analyzing the present situation of archive service of major sports events, especially the analysis of the opposite dependent subjects of service providers and users, we can see that the continuous development of archive services for major sports events will inevitably lead to constant changes in user groups and user needs, guided by the theory of information retrieval, knowledge management, and media effect. According to the service model of archive service of major sports events, the archive service model of specific sports events is constructed. In this paper, four kinds of event recommendation models are applied to the collected marathon event data for experiments. Through experimental comparison, the effectiveness of content-based recommendation algorithm technology in the event network data set is verified, and an algorithm model suitable for marathon event recommendation is obtained. Experiments show that the comprehensive event recommendation model based on term frequency–inverse document frequency (TF-IDF) text weight and Race2vec entry sequence has the best recommendation performance on marathon event data set. According to the recommendation target of the event and the characteristics of the event data type, we can choose a single or comprehensive recommendation algorithm to build a model to realize the event recommendation.
Highlights
Under the background of big data and artificial intelligence, sports and big data are in urgent need of integration and development, and the increment of sports-related information, especially sports information resources on the Internet platform, has risen sharply
This paper analyzes the characteristics of the current network event information to select the appropriate data recommendation algorithm, through the combination of algorithm and data to build a practical event recommendation model, in order to provide the basis and reference for the application research of fragmented sports information resources represented by competition Internet data and the use of related methods
The event recommendation model constructed in this paper is based on the analysis of network data characteristics of events, which makes it clear that the current network data of events has the characteristics of large amount of text data and uneven and diversified data distribution
Summary
Under the background of big data and artificial intelligence, sports and big data are in urgent need of integration and development, and the increment of sports-related information, especially sports information resources on the Internet platform, has risen sharply. This paper analyzes the characteristics of the current network event information to select the appropriate data recommendation algorithm, through the combination of algorithm and data to build a practical event recommendation model, in order to provide the basis and reference for the application research of fragmented sports information resources represented by competition Internet data and the use of related methods It gives the possibility of integration and development of sports event information and related information technology from the perspective of technology, which provides a broader idea for sports informationization research and enriches the technical means of sports research. Archive service providers must constantly develop service infrastructure, change service concepts, and innovate service methods: build an objective foundation of archive service that adapts to the development of the times and can continuously integrate new technologies, new equipment, and new concepts
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