Method for Calculating Text Similarity Of Cross-Weighted Products Applied To Power Grid Model Search

the ranking of search results in grid model search uses the method of ranking by comprehensive score from high to low. The comprehensive score is calculated by multi-field comprehensive text similarity score, filter matching score, and attention score, calculated according to a certain percentage. The basis of the multi-field comprehensive text similarity algorithm is the similarity calculation method of short text, which needs to be flexibly adjusted according to the characteristics of various fields of data in the grid model. Therefore, a short text similarity calculation method with certain adjustability is designed. The algorithm constructs two weight arrays with the same length as the two short text that need to be calculated for similarity and assigns the initial weight value, then traverses the characters in one of the strings, and adjusts their weight according to whether they exist in another, then calculates the weight cross product of single word matching and continuous matching characters to obtain the text similarity weight, and obtains the text similarity value by dividing the product of the two original text total weights. The result of grid model search based on the cross similarity algorithm is closer to the expectation of power system users in terms of the accuracy of search results.