Parental Involvement (PIV), student value mathematics (SVM), students like mathematics (SLM), students confident in mathematics (SCM), Teacher responsiveness (TRES), positively worded items (pos), negatively worded items (neg).
The required conditional probabilities of phrase expansion are easily estimated if a large corpus annotated with phrase bracketings (a treebank) is available (though estimates of POS → word expansion probabilities are best supplemented with additional data).
Part of speech (POS): The POS tag of word w denotes whether word w is a noun, verb, adjective or a different POS.
POS Target words Most-agreed upon labels All agreed-upon words Noun 250 271 1328 Verb 98 65 488 Adj. 14 4 117 Adv.
groups POS-tagged words into the noun phrases using the set of rules and the lexicon.
The sequence of words between the two entities; Types of entities (Person, Organization, Location etc).; POS tag of each word; POS tags of the sequence of words between the two entities; The number of words separating the two entities; The head of the segment;2.
where t i is word pos candidate and t 0 is the beginning pos the sequence specially.
Xia et al. [24] design two types of feature sets: POS based and word relation based.
We denote the mutation context of mutation mut in position pos of the word W as { mut | pos, W}.
Features extracted from review text (e.g., bag of words, POS tags) are often used to train spam detection classifiers.
Among the set of features utilized, genre and number of the words, POS, and syntactic structures such as appositive, head of the sentence, and others stand out.
