CCNU at TAC 2008: Proceeding on Using Semantic Method for Automated Summarization Yield

The CCNU summarization system, PUSMS (Proceeding to Using Semantic Method for Summarization), join in TAC (formerly DUC) for the first time. For the update summarization tasks, we used syntacticbased anaphora resolution and sentence compression algorithms in our system. Term significance was then obtained by frequency-related topic significance and query-related significance by obtaining cooccurrence information with query terms. For the pilot QA summarization task, a semantic orientation recognition module which used WordNet::Similarity::Vector to obtain all of the main part-of-speech terms’ similarity with benchmark words derived from General Inquirer is used in PUSMS pilot system. We also developed a document classifier and a snippets-related content extracting module for the pilot tasks. In all, our initial job can be boiled down to be introducing semantic method into our former statistical summarization system. By analyzing the evaluation results, we found that we were preceding the right target but still have a long way to go.