Automatically summarising topics in a collection of electronic documents

A system for detecting and summarising at least one topic in at least one document of a document set, each document in said document set having a plurality of terms and a plurality of sentences comprising said plurality of terms, wherein said plurality of terms and said plurality of sentences are represented as a plurality of vectors in a two-dimensional space, said system comprising:

• means for pre-processing said at least one document to extract a plurality of significant terms and to create a plurality of basic terms;
• means for formatting said at least one document and said plurality of basic terms;
• means for reducing said plurality of basic terms;
• means for reducing said plurality of sentences;
• means for creating a matrix of said reduced plurality of basic terms on said reduced plurality of sentences;
• means for utilising said matrix to correlate said plurality of basic terms;
• means for transforming a two-dimensional coordinate associated with each of said correlated plurality of basic terms to an n-dimensional co-ordinate;
• means for clustering said reduced plurality of sentence vectors in said n-dimensional space;
• and
• means for associating magnitudes of said reduced plurality of sentence vectors with said at least one topic.

Computer readable code stored on a computer readable storage medium for detecting and summarising at least one topic in at least one document of a document set, each document in said document set having a plurality of terms and a plurality of sentences comprising said plurality of terms, said computer readable code comprising:

• first processes for pre-processing said at least one document to extract a plurality of significant terms and to create a plurality of basic terms;
• second processes for formatting said at least one document and said plurality of basic terms;
• third processes for reducing said plurality of basic terms;
• fourth processes for reducing said plurality of sentences;
• fifth processess for creating a matrix of said reduced plurality of basic terms and said reduced plurality of sentences;
• sixth processes for utilising said matrix to correlate said plurality of basic terms;
• seventh processes for transforming a two-dimensional coordinate associated with each of said correlated plurality of basic terms to an n-dimensional coordinate;
• eighth processess for clustering said reduced plurality of sentence vectors in said n-dimensional space;
• and
• ninth processes associating magnitudes of said reduced plurality of sentence vectors with said at least one topic.