Information Retrieval by Unknown

Author:Unknown
Language: eng
Format: epub
ISBN: 9783030567255
Publisher: Springer International Publishing

(6)

where is parameter need to learn, and aggregates one matrix by columns into a single vector.

3.4 Learning and Prediction

Finally, by considering all facts and their label sets, we obtain our learning approach as follows:

(7)

where is each negative label mined from siblings of y. We use the Adam optimizer and update the parameters of our model for each iteration according to Eq.(7).

To summarize, the matching strategy can be described as: for all article labels, we first generate their representations through GCN model. Based on the fixed label representations, given a fact x, the best label set is a combination of assignments with the highest score from each label given the input:

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