Discourse-Level Structure in Abstracts.
Elizabeth D. Liddy · 1987
An investigation was undertaken into the possibility of automatically detecting how concepts exist in relation to each other in abstracts, a next -type commonly used in free-text retrieval. The end goal of this research is to capture these relationships in structured representations of abstracts' contents so that users can require not only that the concepts of interest to them co-occur in the retrieved documents, but also that the roles they play in relation to one another are the ones of interest. Four tasks found useful in revealing other schema were performed by expert abstractors. The results were analyzed and used as the basis for developing a frame-like structure of abstracts reporting on empirical work. A discourse linguistic analysis of a sample of 276 abstracts identified the lexical/syntactic clues which could be used by a system to automatically instantiate the frame-like structure of individual abstracts. The text is supplemented by four tables and three figures. (10 references) (Author) *********************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. *********************************************************************** U ; DEPARTMENT OF EDUCATION Othce Ulu:AN:ma, Research and trnproverne^t EDUCATIONAL RESOURCES INFORMATION CENTER ERIC' Ths document has been revfoducep ,,s ,ecer.ed ',Om the CeS0h orgar,:a.,on encpnaeng .1 C Mawr changes na.e been age to mprove reproduCeOn Qualay Fonts of.rep, or 000,ons State(' n1,5 Coc a.e., rernssaroy represent oft.c.a. OERI Doshon or Vel Cy DISCCURSE-LEVEL STRUCTURE IN ABSTRACTS Elizabeth D. Liddy ;yracuse University, School of Information Studies, Syracuse, Abstract. An inveat.:ation was undertaken into the possibility of automatically detecting how concepts exist in relationship to each other in abstracts. a text-type commonly used in free-text retrieval. The end goal of this research is to capture these relationships in structured representations of abstracts' contents so that users can require not only that the concepts of interest to them co-occur in the retrieved documents. but also that the roles they play in relation to each other are the ones of interest. Four taske found useful in revealing other schema were performed by expert abetractore. The results were analyzed and used as the basis of developing a frame-like structure of abstracts reporting on empirical work. A diecourse linguistic analysis of a sample of 276 abstracts identified the lexical/syntactic clues which could be used by a system to automatically instantiate the frame-like structure of individual abstracts. An inveat.:ation was undertaken into the possibility of automatically detecting how concepts exist in relationship to each other in abstracts. a text-type commonly used in free-text retrieval. The end goal of this research is to capture these relationships in structured representations of abstracts' contents so that users can require not only that the concepts of interest to them co-occur in the retrieved documents. but also that the roles they play in relation to each other are the ones of interest. Four taske found useful in revealing other schema were performed by expert abetractore. The results were analyzed and used as the basis of developing a frame-like structure of abstracts reporting on empirical work. A diecourse linguistic analysis of a sample of 276 abstracts identified the lexical/syntactic clues which could be used by a system to automatically instantiate the frame-like structure of individual abstracts.