Patent ID: 11922120
Assignee: KOA HEALTH DIGITAL SOLUTIONS S.L.U.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 1:
2. A method for autocompleting a textual input of a user, comprising:
receiving the textual input of the user via a user interface of a smartphone of the user;
generating a situational parameter relating to the user based on the textual input and on sensor data from a user sensor;
generating a temporal parameter based on the textual input and on the sensor data;
retrieving from a storage device historical textual input and historical sensor data relating to the situational parameter and the temporal parameter;
aggregating the historical textual input and the historical sensor data relating to the situational parameter and the temporal parameter;
selecting a situational value relating to the situational parameter based on the historical textual input and the historical sensor data that has been aggregated;
generating a first list of words that the user is likely to input next based on the situational value that has been selected, wherein the words relate to the situational parameter;
ranking the words of the first list by probability that the user is intending to type each of the words;
displaying to the user on the user interface a word ranked highest on the first list;
defining a time window in the past based on the situational parameter and the temporal parameter;
determining whether, for the user, a pre-existing model exists that relates the situational parameter to the time window;
using the pre-existing model, if the pre-existing model exists, to select the situational value relating to the situational parameter based on the historical textual input and the historical sensor data that has been aggregated;
aggregating the historical textual input and the historical sensor data relating to the situational parameter, if no pre-existing model exists, in time slots of equal length to the time window;
creating a language model, if no pre-existing model exists, using the historical textual input and the historical sensor data that has been aggregated; and
selecting, if no pre-existing model exists, the situational value relating to the situational parameter using the language model that has been created.