Abstract: The present disclosure relates to a system, a method, and a product for topic discovery. The system includes a memory storing instructions; and a processor in communication with the memory. When the processor executes the instructions, the instructions are configured to cause the processor to: obtain text data, conduct pre-processing on the text data to obtain pre-processed text data, extract an entity list and a keyword list based on the pre-processed text data, generate an entity embedding list based on the entity list, clusterize the entity list based on the entity embedding list to obtain a plurality of entity clusters, each entity cluster comprising at least one entity, retrieve a co-occurring keyword list based on the plurality of entity clusters, the entity list, and the keyword list, and obtain a topic for each entity cluster of the plurality of entity clusters based on the co-occurring keyword list.

Abstract: A contract platform may receive, from data structures, historical contract data; read, from the historical contract data, numerical categorical data; process the numerical categorical data, with one or more artificial intelligence models, to convert the numerical categorical data into vector format; generate a taxonomy in vector format based on the converted numerical categorical data; read, from the historical contract data, nonnumerical noncategorical data; process the nonnumerical noncategorical data, with the models, to convert the nonnumerical noncategorical data into vector format; generate a knowledge graph in vector format based on the converted nonnumerical noncategorical data.

Abstract: A sleep monitoring system includes an ECG device (2) and a respiration inductance plethysmogram (3) which monitor cardiac activity and physical (ribcage) respiration respectively and feed representative signals to a digital data processor. Operations (5-9) process the beat interval data, while in a second thread, operations (20-24) independently process the amplitude modulation of the ECG data caused by the respiratory motion of the subject. The inductance plethysmogram device (3) provides an input to the processor which represents respiration as directly monitored independently of the ECG. Operations (30-34) process this direct respiration data independently and in parallel, in a third thread. All extracted features are fed to a classifier which in step (10) combines selected combinations of features to make decisions in real time.

Abstract: A sleep monitoring system includes an ECG device (2) and a respiration inductance plethysmogram (3) which monitor cardiac activity and physical (ribcage) respiration respectively and feed representative signals to a digital data processor. Operations (5-9) process the beat interval data, while in a second thread, operations (20-24) independently process the amplitude modulation of the ECG data caused by the respiratory motion of the subject. The inductance plethysmogram device (3) provides an input to the processor which represents respiration as directly monitored independently of the ECG. Operations (30-34) process this direct respiration data independently and in parallel, in a third thread. All extracted features are fed to a classifier which in step (10) combines selected combinations of features to make decisions in real time.

Abstract: A contract platform may receive, from data structures, historical contract data; read, from the historical contract data, numerical categorical data; process the numerical categorical data, with one or more artificial intelligence models, to convert the numerical categorical data into vector format; generate a taxonomy in vector format based on the converted numerical categorical data; read, from the historical contract data, nonnumerical noncategorical data; process the nonnumerical noncategorical data, with the models, to convert the nonnumerical noncategorical data into vector format; generate a knowledge graph in vector format based on the converted nonnumerical noncategorical data.

Abstract: A sleep monitoring system includes an ECG device and a respiration inductance plethysmogram which monitor cardiac activity and physical respiration respectively and feed representative signals to a digital data processor. Operations process the beat interval data, while in a second thread, operations independently process the amplitude modulation of the ECG data caused by the respiratory motion of the subject. The inductance plethysmogram device provides an input to the processor which represents respiration as directly monitored independently of the ECG. Operations process this direct respiration data independently and in parallel, in a third thread. All extracted features are fed to a classifier which in step combines selected combinations of features to make decisions in real time.

Abstract: A sleep monitoring system includes an ECG device (2) and a respiration inductance plethysmogram (3) which monitor cardiac activity and physical (ribcage) respiration respectively and feed representative signals to a digital data processor. Operations (5-9) process the beat interval data, while in a second thread, operations (20-24) independently process the amplitude modulation of the ECG data caused by the respiratory motion of the subject. The inductance plethysmogram device (3) provides an input to the processor which represents respiration as directly monitored independently of the ECG. Operations (30-34) process this direct respiration data independently and in parallel, in a third thread. All extracted features are fed to a classifier which in step (10) combines selected combinations of features to make decisions in real time.

Abstract: A sleep monitoring system includes an ECG device (2) and a respiration inductance plethysmogram (3) which monitor cardiac activity and physical (ribcage) respiration respectively and feed representative signals to a digital data processor. Operations (5-9) process the beat interval data, while in a second thread, operations (20-24) independently process the amplitude modulation of the ECG data caused by the respiratory motion of the subject. The inductance plethysmogram device (3) provides an input to the processor which represents respiration as directly monitored independently of the ECG. Operations (30-34) process this direct respiration data independently and in parallel, in a third thread. All extracted features are fed to a classifier which in step (10) combines selected combinations of features to make decisions in real time.

Abstract: A sleep monitoring system includes an ECG device (2) and a respiration inductance plethysmogram (3) which monitor cardiac activity and physical (ribcage) respiration respectively and feed representative signals to a digital data processor. Operations (5-9) process the beat interval data, while in a second thread, operations (20-24) independently process the amplitude modulation of the ECG data caused by the respiratory motion of the subject. The inductance plethysmogram device (3) provides an input to the processor which represents respiration as directly monitored independently of the ECG. Operations (30-34) process this direct respiration data independently and in parallel, in a third thread. All extracted features are fed to a classifier which in step (10) combines selected combinations of features to make decisions in real time.