Topic identification based on functional summarization

A method to identify a topic for a document, the method comprising:

• applying a plurality of summarization engines to the document to provide a summary of the document;
• applying at least one meta-algorithmic pattern to at least two summaries to provide a meta-summary of the document using the at least two summaries;
• identifying, from the meta-summaries, topics associated with the document;
• retrieving a collection of topic dimensions from a repositor of topic dimensions;
• mapping the identified topics to the topic dimensions in the collection of topic dimensions;
• identifying a representative point based on the identified topics;
• determining distance measures of the representative point from topic dimensions in the collection of topic dimensions, the distance measures indicative of proximity of respective topic dimensions to the representative point;
• and
• selecting a topic dimension to be associated with the document, the selection based on optimizing the distance measures.

A non-transitory computer readable medium comprising executable instructions to:

• receive, via a computing device, a document to be associated with a topic;
• apply a plurality of summarization engines to the document to provide a summary of the document;
• apply relative weights to at least two summaries to provide a meta-summary of the document using the at least two summaries, wherein the relative weights are determined based on one of proportionality to an inverse of a topic identification error, proportionality to accuracy squared, a normalized weighted combination of these, an inverse of a square root of the topic identification error, and a uniform weighting scheme;
• identify, from the meta-summaries, topics associated with the document;
• map the identified topics to the topic dimensions in a collection of topic dimensions retrieved from a repository, of topic dimensions;
• identify a representative point of the identified topics;
• determine distance measures of the representative point from topic dimensions in the collection of topic dimensions, the distance measures indicative of proximity of respective topic dimensions to the representative point;
• and
• select a topic dimension to be associated with the document, the election based on optimizing the distance measures.