CPC G06F 40/30 (2020.01) [G06F 16/35 (2019.01); G06F 40/295 (2020.01)] | 9 Claims |
1. A method for processing a sematic description of a text entity, comprising:
acquiring a plurality of target texts containing a main entity, and extracting related entities describing the main entity from each target text;
acquiring a sub-relation vector of a pair of the main entity and each related entity in each target text;
calculating a similarity distance of the main entity between different target texts based on the sub-relation vector; and
determining a semantic similarity of the main entity descripted in different target texts based on the similarity distance,
wherein the acquiring the sub-relation vector of the pair of the main entity and each related entity in each target text comprises:
acquiring a first vector representation of each word in the target text;
weighting the first vector representation, the main entity, and each related entity based on a pre-trained conversion model, and acquiring a second vector representation of a text content associated with the main entity and each related entity in the target text; and
performing a pooling process on the second vector representation to generate the sub-relation vector of the pair of the main entity and each related entity.
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