Summarization is one of the key features of human intelligence. It plays an important role in understanding and representation. With rapid and continual expansion of texts, pictures and videos in cyberspace, automatic summarization becomes more and more desirable. Text summarization has been studied for over half century, but it is still hard to automatically generate a satisfied summary. Traditional methods process texts empirically and neglect the fundamental characteristics and principles of language use and understanding. This paper summarizes previous text summarization approaches in a multi-dimensional classification space, introduces a multi-dimensional methodology for research and development, unveils the basic characteristics and principles of language use and understanding, investigates some fundamental mechanisms of summarization, studies the dimensions and forms of representations, and proposes a multi-dimensional evaluation mechanisms. Investigation extends to the incorporation of pictures into summary and to the summarization of videos, graphs and pictures, and then reaches a general summarization framework. Further, some basic behaviors of summarization are studied in the complex space consisting of cyberspace, physical space and social space. The basic viewpoints include: (1) a representation suitable for summarization should have a core, indicated by its intention and extension; (2) summarization is an open process of various interactions, involved in various explicit and implicit citations; and, (3) the form of summary is diverse and summarization carries out through multiple dimensions.
Recently, a general summarization approach based on the definition of general citation was proposed REF .
Dimensionality on Summarization
ArXiv
ArXiv
Computer Science