Frequency is a noun.
The word inventions is a noun. It is the plural form of invention.
For this you will need a node structure that stores a word and its frequency. The frequency is initially 1 (one), and the constructor should just accept the word. You then create a list from this structure. As you parse the text, extract each word and search the list. If the word does not exist, push a new structure for the word onto the list, otherwise increment the frequency for the word. When you've parsed the file, you will have your frequency count for each word in the list. The basic structure for each node is as follows (you may wish to embellish it further by encapsulating the word and its frequency). struct node { std::string m_word; unsigned long long m_freq; node(std::string wrd): m_word(wrd), m_freq(1) {} }; When parsing your text, remember to ignore whitespace and punctuation unless it is part of the word (such as contractions like "wouldn't"). You should also ignore capitalisation unless you wish to treat words like "This" and "this" as being separate words.
subject
frequency
This is the most straight-forward approach to working with quantitative data. Items are classified according to a particular scheme and an arithmetical count is made of the number of items (ortokens) within the text which belong to each classification (or type) in the scheme.For instance, we might set up a classification scheme to look at the frequency of the four major parts of speech: noun, verb, adjective and adverb. These four classes would constitute our types. Another example inolves the simple one-to-one mapping of form onto classification. In other words, we count the number of times each word appears in the corpus, resulting in a list which might look something like:abandon: 5abandoned: 3abandons: 2ability: 5able: 28about: 128etc.....More often, however, the use of a classification scheme implies a deliberate act of categorisation on the part of the investigator. Even in the case of word frequency analysis, variant forms of the same lexeme may be lemmatised before a frequency count is made. For instance, in the example above, abandon, abandons and abandoned might all be classed as the lexeme ABANDON. Very often the classification scheme used will correspond to the type of linguistic annotation . An example of this might be an analysis of the incidence of different parts of speech in a corpus which had already been part-of-speech tagged.
The word never is an adverb (of frequency). It means under no circumstances.
The word never is an adverb (of frequency). It means under no circumstances.
An adverb, an adverb of frequency, because it tells how often you did the verb.
The part of speech for this particular word is a noun.
The part of speech that the word my is used as is an adjective.
H is a letter, not a word. To be a part of speech, it needs to be a word.
The part of speech for the word civilian is English grammar.
The part of speech for the word diplomacy is a noun.
The word speech is a noun.
The part of speech for this particular word is a noun.
The word speech is a noun.
The word speech is a noun.