Systems, methods and computer program products for building a database associating n-grams with cognitive motivation orientations

A database-building data processing system configured for building an analysis database associating each of a plurality of n-grams with corresponding respective cognitive motivation orientations, the system comprising:

• a host computer with memory and at least one processor coupled to the memory;
• and
• a database-building module, the database-building module comprising program code that, when executed in the memory of the host computer:
• receives a training corpus of training documents, wherein:
• each training document comprises a plurality of meaningfully arranged words in electronic form;
• each training document has at least one annotated word sequence therein;
• wherein within each training document, each particular annotated word sequence is annotated with a corresponding word-sequence-level annotation identifying at least one cognitive motivation orientation that is associated with that particular annotated word sequence;
• for each training document:
• for each annotated word sequence in that particular training document:
• extracts n-grams overlapping that particular annotated word sequence;
• and
• associates each extracted n-gram with the at least one cognitive motivation orientation associated with that particular annotated word sequence;
• generates a set of indicator candidate n-grams wherein:
• each indicator candidate n-gram represents all instances of a particular n-gram in the training corpus for which at least one instance of that particular n-gram was extracted from any annotated word sequence in any training document;
• each indicator candidate n-gram being associated with every cognitive motivation orientation that is associated with at least one instance of the particular n-gram represented by that particular indicator candidate n-gram;
• applies at least one relevance filter to each indicator candidate n-gram in the set of indicator candidate n-grams to obtain a set of indicator n-grams, wherein;
• the set of indicator n-grams is a subset of the set of indicator candidate n-grams, so that each indicator n-gram corresponds to only one indicator candidate n-gram and thereby each indicator n-gram represents all instances of a corresponding particular n-gram in the training corpus for which at least one instance of that particular n-gram was extracted from any annotated word sequence in any training document;
• and
• each indicator n-gram is associated with only a single cognitive motivation orientation;
• wherein each indicator n-gram has, as its associated single cognitive motivation orientation, that single cognitive motivation orientation with which the instances of the particular n-gram represented by that particular indicator n-gram are most frequently associated.

A computer program product for building an analysis database associating each of a plurality of n-grams with corresponding respective cognitive motivation orientations, the computer program product comprising:

• a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising:
• computer readable program code adapted to, when executed by a computer, cause the computer to receive a training corpus of training documents, wherein:
• each training document comprises a plurality of meaningfully arranged words in electronic form;
• each training document has at least one annotated word sequence therein;
• wherein, within each training document, each particular annotated word sequence is annotated with a corresponding word-sequence-level annotation identifying at least one cognitive motivation orientation that is associated with that particular annotated word sequence;
• computer readable program code adapted to, when executed by a computer, cause the computer to, for each training document:
• for each annotated word sequence in that particular training document:
• extract n-grams overlapping that particular annotated word sequence;
• and
• associate each extracted n-gram with the at least one cognitive motivation orientation associated with that particular annotated word sequence;
• computer readable program code adapted to, when executed by a computer, cause the computer to generate indicator candidate n-grams wherein:
• each indicator candidate n-gram represents all instances of a particular n-gram in the training corpus for which at least one instance of that particular n-gram was extracted from any annotated word sequence in any training document;
• each indicator candidate n-gram being associated with every cognitive motivation orientation that is associated with at least one instance of the particular n-gram represented by that particular indicator candidate n-gram;
• computer readable program code adapted to, when executed by a computer, cause the computer to apply at least one relevance filter to each indicator candidate n-grams in the set of indicator candidate n-grams to obtain a set of indicator n-grams, wherein;
• the set of indicator n-grams is a subset of the set of indicator candidate n-grams, so that each indicator n-gram corresponds to only one indicator candidate n-gram and thereby each indicator n-gram represents all instances of a corresponding particular n-gram in the training corpus for which at least one instance of that particular n-gram was extracted from any annotated word sequence in any training document;
• and
• each indicator n-gram is associated with only a single cognitive motivation orientation;
• wherein each indicator n-gram has, as its associated single cognitive motivation orientation, that single cognitive motivation orientation with which the instances of the particular n-gram represented by that particular indicator n-gram are most frequently associated.