  Formal Semantics and Distributional Semantics are two important semantic
frameworks in Natural Language Processing (NLP). Cognitive Semantics belongs to
the movement of Cognitive Linguistics, which is based on contemporary cognitive
science. Each framework could deal with some meaning phenomena, but none of
them fulfills all requirements proposed by applications. A unified semantic
theory characterizing all important language phenomena has both theoretical and
practical significance; however, although many attempts have been made in
recent years, no existing theory has achieved this goal yet.
  This article introduces a new semantic theory that has the potential to
characterize most of the important meaning phenomena of natural language and to
fulfill most of the necessary requirements for philosophical analysis and for
NLP applications. The theory is based on a unified representation of
information, and constructs a kind of mathematical model called cognitive model
to interpret natural language expressions in a compositional manner. It accepts
the empirical assumption of Cognitive Semantics, and overcomes most
shortcomings of Formal Semantics and of Distributional Semantics. The theory,
however, is not a simple combination of existing theories, but an extensive
generalization of classic logic and Formal Semantics. It inherits nearly all
advantages of Formal Semantics, and also provides descriptive contents for
objects and events as fine-gram as possible, descriptive contents which
represent the results of human cognition.
