Design of Pitch Control Software Infrastructure Based on Collaborative Filtering Algorithm.

The pitch control of electronic equipment is the overall and key problem of electronic equipment system. The traditional pitch control of electronic equipment mainly depends on the volume control table, but this method depends too much on the hardware design, the corresponding pitch control effect is relatively unstable, and the cost is high. Based on the research of traditional pitch control software, this project improves the collaborative filtering algorithm and reduces the range of nearest neighbour set of pitch samples by introducing clustering algorithm, to further shorten the search time of neighbour set and finally improve the real time and scalability of the system. To adapt to the environment and user preferences, this study proposes to calculate the attributes between different items when improving the collaborative filtering algorithm, so as to further determine the unique attributes between items and determine the similarity between items, so as to introduce the pitch preference correction factor based on user attributes, so as to realize the high precision of electronic equipment based on pitch control software preference recommendation setting. Based on this, this project takes the improved collaborative filtering algorithm as the core algorithm to build a set of digital TV pitch control software system and realizes the verification of the algorithm proposed in this study based on MATLAB simulation software. The experimental results show that the pitch control accuracy of the algorithm is about 10% higher than that of the traditional algorithm. In terms of the intelligence of the corresponding algorithm, the algorithm proposed in this study has obvious advantages compared with the traditional algorithm. At the same time, its intelligent recommendation to users also has high intelligence, and the corresponding intelligent recommendation rate is about 4%–10% higher than that of the traditional algorithm, which proves that the algorithm in this study has obvious advantages. [ABSTRACT FROM AUTHOR]