IJSEA Volume 12 Issue 2

Clustering and Mining Algorithm of Factor Structure Data of Physical Education Teachers' Teaching Behavior Based on Internet Information Retrieval Algorithm

Bo Liu
10.7753/IJSEA1202.1004
keywords : Clustering and Mining Algorithm, Factor Structure Data, Physical Education, Information Retrieval Algorithm

PDF
Integrating visual word list and Rocchio algorithm, constructs an implicit relevance feedback retrieval model in semantic space, and judges information retrieval preference. User demand mining is introduced, Jensen-Shannon divergence is used to calculate the relative entropy distance between the probability distributions of document sets, and similarity matching is calculated to complete interactive information retrieval. Teaching ability is gradually formed by teachers in long-term teaching practice, and is stably and comprehensively reflected in teaching viewpoints, teaching methods, teaching skills, teaching style and so on. The weight analysis of each index in the evaluation index system was carried out by using the analytic hierarchy process, and the selection of the evaluation subject was completed through the third round of expert questionnaires, and the evaluation criteria were formulated in combination with the opinions of tutors and some expert teachers.
@artical{b1222023ijsea12021004,
Title = "Clustering and Mining Algorithm of Factor Structure Data of Physical Education Teachers' Teaching Behavior Based on Internet Information Retrieval Algorithm",
Journal ="International Journal of Science and Engineering Applications (IJSEA)",
Volume = "12",
Issue ="2",
Pages ="10 - 12",
Year = "2023",
Authors ="Bo Liu"}