Research Article
Recognition of Hotspot Words for Disease Symptoms Incorporating Contextual Weight and Co-Occurrence Degree
| | Symbol | Description |
| | d | Disease description | | D | The set of disease descriptions | | Em | Masked vector for d | | Eo | Original vector for d | | MeanSemSim (w, d) | The mean value of semantic similarity between w and words in d | | TF-IDF (w, d, D) | The value of TF-IDF for the word w in d | | α | The weight balance factor | | si | The ith disease symptom word | | G | Disease symptom word association graph | | si↔sj. | si and sj satisfy co-occurrence association | | Nco (si, sj) | The weight of the co-occurrence edge | | vi(K) | Vector feature representation of the ith node in the Kth time step | | P(K) | The predicted value at Kth time step | | pi | The output result corresponding to the ith node | | L(K) | The loss at Kth time step |
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