So while brainstorming on the potential to assemble lists, pre·lim·i·nar·i·ly, based on keywords, I’ve been able to at least break down the areas of research that need to be addressed.
The “Topic” name, as described by the end user will need to be accurate when using an approach of duality.
That is to say, if a list of Dogs exists (pardon the canine references), but if the end user decides to call the list something like “Animals”, or some other word that is less specific, and doesn’t describe the list accurately, using a common vocabulary word, then the needle in a haystack approach of using keyword intersections isn’t going to work.
But what do I mean by keyword intersections?
Well specifically, the intersection function in PHP exists, where you can specify a list of keywords as an array in a call to the intersection function.
$result = intersect ($array1, $array2);
Using this approach we can specify the keyword definitions as words of arrays, which are actually in the case of Dogs the definitions for each of the dogs (reducing prepositions, or other non-related grammar).
So we would have the Airedale array, the Puli Array, the Yorkshire Terrier Array, etc.
The idea then would be by taking the intersection of the definitions of the dogs, and coupling also the Topic name, to each array, it could be reasoned that a decent Topic name could be derived. The common word (from the Topic Name), is the game changer. However this doesn’t always work.
Say we generalize a list as “Animals”, and use the same logic. Then, as definitions of various animals are given (via the online dictionary), then it should be noted that these definitions should follow a certain criterion when describing an animal – and for most dictionaries, unfortunately, this is not the case.
So then what might be proposed, is to control the dictionary and pre-modify it to yield key constructs that would best give us the intentional intersect best describing the Keyword Topic (independent from the actual end user, having described the list using a Topic Name).
Then when the intersection function is ran, the word MOST COMMON words in each array is selected, and thus identifies in some respect the type of list, or the subject of the list, because inherent in the definitions are common vocabulary words that can help to identify the topic.