The document describes natural language generation techniques for trend descriptions. It discusses generating verbs and adjectives to describe trends based on whether a value increased, decreased, or remained stable compared to a previous value. It also covers generating the grammatical subject of sentences by referring to the topic in different ways while discussing it. Finally, it discusses combining simple sentences into compound and complex sentences to increase variety in generated trend descriptions.

1. Natural language generation of trend descriptions
Generation of verb/noun and
adverb/adjective
The trend verb can be generated by
comparing two values x and y.
e.g.
x < y decrease, drop, fall, plummet
x ≈ y increase, climb, rise,
x > y remained stable, even out
The difference between x and y affects the
choice of verb and the adverb (e.g. slight,
slightly, substantial, substantially)
There was a slight increase in the first quarter.
Generation of
grammatical subject
The basic topic is provided in the
dataset. Take “price of bananas”
as a case in point. The subject for
consecutive sentences is the
same, but needs to be realized
using different words, e.g.
The price of bananas
The price
It
Generation of sentence
variety
The initial algorithm creates
simple sentences. Sentences
need to be combined to form
compound and/or complex
sentences.
Users dropped to 250 in Q2, then
rose by 30 in Q3, peaking at 390
in Q4.