Semantic Graph Based Automatic Text Summarization for Hindi Documents Using Particle Swarm Optimization

Automatic text summarization can be defined as a process of extracting and describing important information from given document using computer algorithms. A number of techniques have been proposed by researchers in the past for summarization of English text. Automatic summarization of Indian text has received a very little attention so far. In this paper, we propose an approach for summarizing Hindi text based on semantic graph of the document using Particle Swarm Optimization (PSO) algorithm. PSO is one of the most powerful bio-inspired algorithms used to obtain optimal solution. The subject-object-verb (SOV) triples are extracted from the document. These triples are used to construct semantic graph of the document. A classifier is trained using PSO algorithm which is then used to generate semantic sub-graph and to obtain document summary.