Automatic multidocument summarization of research abstracts: design and user evaluation

The purpose of this study was to develop a method for automatic construction of multi-document summaries of sets of research abstracts that may be retrieved by a digital library or search engine in response to a user query. Sociology dissertation abstracts were selected as the sample domain in this study. A variable-based framework was proposed for integrating and organizing research concepts and relationships as well as research methods and contextual relations extracted from different dissertation abstracts. Based on the framework, a new summarization method was developed, which parses the discourse structure of abstracts, extracts research concepts and relationships, integrates the information across different abstracts, and organizes and presents them in a Web-based interface. A user evaluation was performed to assess the overall quality and usefulness of the summaries. Two types of variable-based summaries generated using the summarization method – with or without the use of a taxonomy – were compared against a sentence-based summary that only lists the research objective sentences extracted from each abstract and another sentence-based summary generated using the MEAD system that extracts important sentences. The evaluation results indicated that the majority of sociological researchers (70%) and general user (64%) preferred the variable-based summaries generated with the use of the taxonomy