Adaptive logistics platform for generating and updating schedules using natural language processing

A method, comprising:

• receiving, by a device, internal preference data associated with one or more bookable items;
• obtaining, by the device, external preference data associated with the one or more bookable items,
• the external preference data being different from the internal preference data, and
• the external preference data being obtained by extracting text from an external source;
• parsing, by the device, the text using natural language processing;
• determining, by the device and based on parsing the text using natural language processing, one or more scores associated with the one or more bookable items;
• generating, by the device, a list of schedules based on the internal preference data and the external preference data;
• generating, by the device, one or more category scores for a plurality of schedules included in the list of schedules based on the one or more scores associated with the one or more bookable items;
• ranking, by the device, the list of schedules based on the one or more category scores;
• selecting, by the device, a first schedule of the ranked list of schedules;
• generating, by the device, a knowledge graph based on the ranked list of schedules,
• the knowledge graph including node values and edge values,
• each node value, of the node values, representing a schedule of the plurality of schedules, and
• each edge value, of the edge values, representing a degree of similarity between two schedules represented by two connected nodes;
• monitoring, by the device, contextual data related to the first schedule,
• the contextual data including at least one of:
• information regarding one or more external events,
• information regarding one or more user actions, or
• user location information;
• detecting, by the device and based on monitoring contextual data, a particular event that impacts a bookable item of the one or more bookable items;
• modifying, by the device, the knowledge graph based on detecting the particular event;
• selecting, by the device, a second schedule based on modifying the knowledge graph;
• and
• performing, by the device, one or more actions based on selecting the second schedule,
• the one or more actions including at least one of:
• automatically displaying the second schedule on an interface of a user device,
• automatically purchasing tickets,
• automatically booking transportation,
• automatically booking flights,
• automatically booking reservations, or
• automatically sending reminder notifications.

A non-transitory computer-readable medium storing instructions, the instructions comprising:

• one or more instructions that, when executed by one or more processors, cause the one or more processors to:
• receive user preference data associated with one or more bookable items;
• receive company preference data associated with the one or more bookable items;
• obtain external preference data associated with the one or more bookable items by extracting text, associated with the one or more bookable items, from an external source,
• the external preference data being different from the user preference data and the company preference data;
• parse the text using natural language processing;
• determine, based on parsing the text using natural language processing, one or more scores associated with the one or more bookable items;
• generate a list of schedules based on the user preference data, the company preference data, and the external preference data;
• generate one or more category scores for a plurality of schedules included in the list of schedules based on the one or more scores associated with the one or more bookable items;
• rank the list of schedules based on the one or more category scores;
• select a first schedule, from the ranked list of schedules, based on the one or more category scores;
• generate a knowledge graph based on the ranked list of schedules,
• the knowledge graph including node values and edge values,
• each node value, of the node values, representing a schedule of the plurality of schedules, and
• each edge value, of the edge values, representing a degree of similarity between two schedules represented by two connected nodes;
• monitor contextual data related to the first schedule,
• the contextual data including at least one of:
• information regarding one or more external events,
• information regarding one or more user actions, or
• user location information;
• detect, based on monitoring the contextual data, a particular event that impacts a bookable item of the one or more bookable items;
• modify the knowledge graph based on detecting the particular event;
• select a second schedule based on modifying the knowledge graph;
• and
• perform one or more actions based on selecting the second schedule,
• the one or more actions including at least one of:
• automatically displaying the second schedule on an interface of a user device,
• automatically purchasing tickets,
• automatically booking transportation,
• automatically booking flights,
• automatically booking reservations, or
• automatically sending reminder notifications.