Evaluation Method of Innovative Education Model of E-Commerce Video Live Broadcast Based on Big Data Analysis Technology

Abstract

In the environment of education big data, how colleges and universities make good use of these data not only affects the orderly operation of the whole education and teaching system of colleges and universities. It will also become an inexhaustible driving force to help colleges and universities promote the reform and innovation of the education and teaching system. This paper takes student evaluation data and student online learning data as research objects. Focusing on the teaching operation and students’ autonomous learning, this paper uses the improved k-mode algorithm to cluster analyze the classroom teaching operation. This paper uses neural network algorithm based on machine learning to predict and compare students’ online course learning. It is hoped that it can provide meaningful reference for the construction of teaching management system and the reform and innovation of teaching management system in colleges and universities. Two research works are mainly carried out through the preliminary analysis and transformation of the data of student evaluation of teaching in a certain university. The improved cosine dissimilarity algorithm is used to eliminate the abnormal teaching evaluation data. The normalization method was used to standardize the teaching evaluation data. The traditional k-mode algorithm is used to cluster the teaching evaluation data. Some problems of k-mode algorithm are pointed out, and the traditional k-mode algorithm is improved. Experimental results show that the improved algorithm is more reasonable and effective.

Analysis of Corporate Mergers and Acquisitions: Evidence from Baidu's Acquisition of YY Live

“…The case study technique is a qualitative research strategy created to collect, examine, and interpret data pertaining to actual events and circumstances, offering insightful information about the underlying dynamics and causal elements [5]. The main sources this study uses are public statements, business reports, and post-Merger Integration cases [7]. The case study approach will provide a thorough knowledge of the motivations and strategic choices that went into Baidu's acquisition of YY Live, allowing for a more in-depth investigation of the transaction's goals and purposes.…”

“…The combination with live broadcast can not only convert the precipitation flow into a cash flow channel, but also can quickly improve the company's internal live broadcast ecology through the acquisition of a mature live broadcast enterprise, the company's original business and live broadcast closely together. After the M & A, Baidu will have more business channels and more liquidity channels, which will help to increase the operating income of the company and thus increase the stock of Baidu's own cash flow to carry on other business for Baidu, artificial Intelligence and long video support, for example, make it easier for Baidu to diversify its business [7]. YY's live streaming service can help Baidu further complement content forms other than text and short videos, enrich Baidu's search content targeting and improve the user experience of its search information streaming service, enhance the stickiness of existing products in Baidu.…”