In this era of information explosion, short videos have become a part of people's lives. Every day, we slide the screen on various short video platforms and browse a huge amount of content. Behind all this is a powerful short video algorithm. Today, let's talk about a niche but extremely critical area in the short video algorithm-how to accurately locate and recommend niche content.

Have you ever had such an experience: on the short video platform, you inadvertently brushed a very small but eye-catching video, such as the production of unpopular handicrafts, little-known minority music performances or extremely small documentary clips. These videos are neither traffic explosions nor big V endorsements, but they appear in front of your screen accurately, as if the algorithm has read the preferences in your heart that you didn't even realize. This is the wonder of short video algorithm in niche content recommendation.

To achieve this kind of accurate recommendation, the algorithm can work hard. It will first analyze the massive video content in detail. From the title and introduction of the video to every detail in the picture, the objects in every frame of the picture, and even the melody and rhythm of the background music, the algorithm will disassemble and label them one by one. For example, for a video about ancient knitting technology, the algorithm will identify a lot of information such as the types of knitting tools, knitting techniques, the use of finished products and so on. At the same time, it will also dig deep into the past work styles of video creators and the characteristics of fan groups, and outline the "personality portrait" of this video in all directions.

For the user side, the algorithm regards us as a "subject" that needs to be carefully studied. It always pays attention to every time we like, comment and forward, and even the time we stay on the video page and the speed of sliding the screen can be accurately captured. When we show a little interest in a niche field, such as occasionally praising a video introducing rare plants, the algorithm will detect this subtle signal like a keen hunter. Then, it will combine all kinds of video records we have watched before to analyze what relevant minority content we may be interested in, such as the growing environment of plants, the history of botanical research and so on.

Next, the algorithm began to search the huge video library for treasure videos that meet our niche interests. It will use a complex recommendation model to take all kinds of factors into consideration. For example, the quality of video is the basic threshold, and videos with clear picture quality and smooth editing are more likely to be recommended. At the same time, the algorithm will also consider the activity of creators and the frequency of content updates, because creators who continue to produce high-quality niche content can often better satisfy our desire to explore new knowledge.

Finally, when we open the short video software again, these carefully selected niche videos just appear in our sight. They are like an exclusive surprise gift, which allows us to discover new niche fun in the process of browsing short videos and satisfy our deep pursuit of knowledge and personalization. This is the charm of the short video algorithm, which works silently in the niche field and accurately captures those "good hearts" hidden in the information ocean for us.

（Writer：Ciki）