Phrasal Graph-based Method for Abstractive Vietnamese Paragraph Compression

ABSTRACT

Text compression is the task of identifying the main information in the source text to form a short single sentence. A broad approach is to find a path containing common vertices in the word graph model. The first issue of this approach is that the path finding algorithm can separate words from the phrase expressing a content. This leads to create new sentences having different meaning from the original ones. The second issue is that when an information is expressed by different words or phrases, called co-reference situations. Due to lacking of mechanism for handling this situation, the compression will be missing information. We propose in this paper a method to overcome the above issues. The core of new method is the improved graph model in which each vertex illustrates a phrase with its corresponding Part-of-Speech label. The intersection vertices of branches are results of mechanism for handling co-references. The compressing algorithm reduces the graph and forms the final sentence. We use ROUGE measure to compare with two word graph-based baselines. The experiment result shows that our method creates short sentences containing rich information.

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Index Terms

• Computing methodologies

  • Artificial intelligence

    • Natural language processing

      • Discourse, dialogue and pragmatics

      • Information extraction