UNIS is a system that performs adaptive text summarization. It recognizes genre of input text and employs algorithms optimized for the given genre. This prototype version supports recognition of 3 genres: fiction, academic, and newspaper.
To implement genre recognition we manually distinguished linguistic parameters of texts (such as, for example, distribution of proper nouns and different pronouns) and then conducted a number of experiments using a neural network to fund out parameters specific for each of the three genres.
As soon as you open a text (use leftmost button) it is identified either as fiction, or academic, or newspaper. Press “summarize” (rightmost) button to get a summary. In the left section of the program you can see a list of terms with their weights arranged in descending order. The terms with highest weights are supposed to be the most salient in the given text. Summary size is determined dynamically by the system depending on text structure.
We conducted evaluations comparing summaries produced by UNIS with those ones created by human experts to find out that the quality of newspaper summaries was about 90% percent, while the quality of fiction and academic summaries ranged between 65-70 %.
UNIS can process English texts in .txt format on Windows machines and requires .net framework.
300 MHz processor 0,5 MB free disc space