Abstract: In various embodiments, a method and an apparatus for extracting topic sentences of webpages are provided. The method comprises: obtaining candidate webpages, and a pre-built machine learning model, each candidate webpage contains multiple preselected candidate topic sentences, and each candidate topic sentence includes several word segments; determining word feature values that indicate importance levels of the word segments in each candidate webpage respectively, and inputting the word feature values to the machine learning model to obtain an importance value for each word segment; for each candidate webpage, determining a partial order value for each candidate topic sentence according to the importance values of the word segments included in the candidate topic sentence; and for each candidate webpage, selecting one of the plurality of candidate topic sentences that is associated with a partial order value larger than a preset threshold value as a target topic sentence of the candidate webpage.

Abstract: In various embodiments, a method and an apparatus for extracting topic sentences of webpages are provided. The method comprises: obtaining candidate webpages, and a pre-built machine learning model, each candidate webpage contains multiple preselected candidate topic sentences, and each candidate topic sentence includes several word segments; determining word feature values that indicate importance levels of the word segments in each candidate webpage respectively, and inputting the word feature values to the machine learning model to obtain an importance value for each word segment; for each candidate webpage, determining a partial order value for each candidate topic sentence according to the importance values of the word segments included in the candidate topic sentence; and for each candidate webpage, selecting one of the plurality of candidate topic sentences that is associated with a partial order value larger than a preset threshold value as a target topic sentence of the candidate webpage.