A memory stores therein a document and a plurality of word vectors that are word embeddings respectively computed for a plurality of words. A processor extracts, with respect to one of the words, two or more surrounding words within a prescribed range from one occurrence position where the one word occurs, from the document, and computes a sum vector by adding word vectors corresponding to the surrounding words. The processor determines a parameter such as to predict the surrounding words from the sum vector and the parameter using a machine learning model. The processor stores the parameter as context information for the one occurrence position, in association with the word vector corresponding to the one word.
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