Specificity ranking of text elements and applications thereof

A computer program product for ranking a plurality of text elements comprising:

• a machine readable storage device;
• and
• computer code stored on the machine readable storage device, with the computer code including instructions and data for causing a processor(s) set to perform operations including the following:
• computing, via a word embedding scheme, an embedding vector which locates a first text element of a plurality of text elements to be ranked in an embedding space,
• selecting a set of text fragments from a reference text, with each text fragment containing the first text element and at least one other text element to be ranked,
• for each text fragment, calculating respective distances in the embedding space between the at least one other text element to be ranked, each located in the space by an embedding vector computed via the word embedding scheme, and the first text element to be ranked,
• calculating a specificity score, dependent on the respective distances in the embedding space, for the text element to be ranked, and
• storing the specificity score, with the specificity scores for the plurality of text elements defining a ranking of the text elements by specificity.

A computing system for ranking a plurality of text elements comprising:

• a processor(s) set;
• a machine readable storage device;
• and
• computer code stored on the machine readable storage device, with the computer code including instructions and data for causing the processor(s) set to perform operations including the following:
• computing, via a word embedding scheme, an embedding vector which locates a first text element of a plurality of text elements to be ranked in an embedding space,
• selecting a set of text fragments from a reference text, with each text fragment containing the first text element and at least one other text element to be ranked,
• for each text fragment, calculating respective distances in the embedding space between the at least one other text element to be ranked, each located in the space by an embedding vector computed via the word embedding scheme, and the first text element to be ranked,
• calculating a specificity score, dependent on the respective distances in the embedding space, for the text element to be ranked, and
• storing the specificity score, with the specificity scores for the plurality of text elements defining a ranking of the text elements by specificity.