Research and Design of Key Technology of Vertical Search Engine for Educational Resources

Abstract

This paper explores several key technologies involved in the vertical search engine of educational resources, including the selection of URL seeds, the crawl of hidden web, the decision of relevance between topics and the sorting algorithm of search results. On this basis, we design a result ranking algorithm for educational vertical search engine based on neural network. The algorithm collects the user's usage and evaluation information, and then adjusts the weights, coefficients and thresholds of the neurons in the neural network according to the information. Finally, the search results are sorted, and the situation is approaching the optimal situation.