A proposed new metric for the conceptual diversity of a text
İlknur Dönmez Phd Mehmet Haklıdır Phd
A word may contain one or more hidden concepts. While the "animal" word
evokes many images in our minds and encapsulates many concepts (birds, dogs,
cats, crocodiles, etc.), the `parrot' word evokes a single image (a colored
bird with a short, hooked beak and the ability to mimic sounds). In spoken or
written texts, we use some words in a general sense and some in a detailed way
to point to a specific object. Until now, a text's conceptual diversity value
cannot be determined using a standard and precise technique. This research
contributes to the natural language processing field of AI by offering a
standardized method and a generic metric for evaluating and comparing concept
diversity in different texts and domains. It also contributes to the field of
semantic research of languages. If we give examples for the diversity score of
two sentences, "He discovered an unknown entity." has a high conceptual
diversity score (16.6801), and "The endoplasmic reticulum forms a series of
flattened sacs within the cytoplasm of eukaryotic cells." sentence has a low
conceptual diversity score which is 3.9068.