An Efficient Text Summarizer using Lexical Chains

We present a system which uses lexical chains as an intermediate representation for automatic text summarization. This system builds on previous research by implementing a lexical chain extraction algorithm in linear time. The system is reasonably domain independent and takes as input any text or HTML document. The system outputs a short summary based on the most salient concepts from the original document. The length of the extracted summary can be either controlled automatically, or manually based on length or percentage of compression. While still under development, the system provides useful summaries which compare well in information content to human generated summaries. Additionally, the system provides a robust test bed for future summary generation research. 1 I n t r o d u c t i o n Automatic text summarization has long been viewed as a two-step process. First, an intermediate representation of the summary must be created. Second, a natural language representation of the summary must be generated using the intermediate representation(Sparek Jones, 1993). Much of the early research in automatic text summarization has involved generation of the intermediate representation. The natural language generation problem has only recently received substantial attention in the context of summarization.