Abstract
Lexical chain has been widely used in many NLP areas. However, when using it for Web text summarization, especially for domain-specific text summarization, we got low accuracy results. The main reason is that traditional lexical chains only take nouns into consideration while information of other grammatical parts is missing. We introduce lexical chains of predicates and adjectives (adverbs) respectively. These three types of lexical chains together are called holographic lexical chains (HLCs), which capture most of the information included in the text. A specifically designed construction method for HLC is presented. We applied HLC method to Chinese text summarization and used machine learning methods whose features are adapted to the new method. In a comparative study of Chinese foreign trade texts, we got summarization results with accuracy of 86.88%. Our HLC construction method obtained improvements of 7.02% in accuracy than the known best methods in Chinese text summarization.
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