With the development of network, location-based service architecture is gradually applied to the learning support service system. The purpose of this study is to develop an online learning support system using allocation information service architecture. In this study, the 2019 year of this study was selected as a research material through an online learning support service system within six months. The system architecture of this study is the Browser/Server architecture. Based on this, we analyze the learning result data using the weight setting of the feature attribute and the learning evaluation algorithm. The results show that the improved algorithm based on location-based service architecture can get the best algorithm accuracy when the weight of the whole algorithm is about α = 0.4. For the degree of demand for learning guidance, 16.2% thought it was absolutely necessary and 50.7% thought it was more necessary. And 70.6% of the learners thought that the learning system was not very accurate or generally accurate. It is concluded that the learning support service system of this study has a certain role. It provides a new path to improve the quality of online education learning support service and promotes the development of online education.

As the national economy has entered a stage of rapid development, the national economy and social development have also ushered in the “14th Five-Year Plan,” and the country has also issued support policies to encourage and guide college students to start their own businesses. Therefore, the establishment of an innovation and entrepreneurship platform has a significant impact on China’s economy. This gives college students great support and help in starting a business. The theory of deep learning algorithms originated from the development of artificial neural networks and is another important field of machine learning. As the computing power of computers has been greatly improved, especially the computing power of GPU can quickly train deep neural networks, deep learning algorithms have become an important research direction. The deep learning algorithm is a nonlinear network structure and a standard modeling method in the field of machine learning. After modeling various templates, they can be identified and implemented. This article uses a combination of theoretical research and empirical research, based on the views and research content of some scholars in recent years, and introduces the basic framework and research content of this article. Then, deep learning algorithms are used to analyze the experimental data. Data analysis is performed, and relevant concepts of deep learning algorithms are combined. This article focuses on exploring the construction of an IAE (innovation and entrepreneurship) education platform and making full use of the role of deep learning algorithms to realize the construction of innovation and entrepreneurship platforms. Traditional methods need to extract features through manual design, then perform feature classification, and finally realize the function of recognition. The deep learning algorithm has strong data image processing capabilities and can quickly process large-scale data. Research data show that 49.5% of college students and 35.2% of undergraduates expressed their interest in entrepreneurship. Entrepreneurship is a good choice to relieve employment pressure.

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With the maturity and rapid expansion of social psychology, great progress has been made in the integration of social psychology with other disciplines. From the very beginning, social psychology is destined to have a diversified and multidisciplinary research orientation and disciplinary nature, which also makes it difficult for social psychology to be defined in a single disciplinary field and a single research method. With the rapid development of the Internet, the emergence of cloud computing technology not only facilitates the orientation of psychological research, but also promotes the emergence and development of some new psychological disciplines. Therefore, the purpose of this paper is to study the orientation of social psychology and its current development in the context of cloud computing era. This paper collects, organizes, and integrates the research data of college students’ view of justice from the perspective of social psychology through cloud computing technology, and uses empirical research methods to conduct in-depth research on people’s view of justice in social psychology. This paper collects the data reports of college students on social justice issues through cloud computing technology to make the results more accurate. The experimental results show that nearly 70% of college students pay more attention to social justice issues. This data clearly reflects the optimistic trend of people’s attention to justice issues in social psychology.