tailieunhanh - Báo cáo khoa học: "Towards Interactive Text Understanding"

This position paper argues for an interactive approach to text understanding. The proposed model extends an existing semantics-based text authoring system by using the input text as a source of information to assist the user in re-authoring its content. The approach permits a reliable deep semantic analysis by combining automatic information extraction with a minimal amount of human intervention. the various authoring choices; in each menu the choices are then ranked according to their likelihood, allowing a speedier selection by the author; when the likelihood of a choice exceeds a certain threshold, this choice is performed automatically by. | Towards Interactive Text Understanding Marc Dymetman Aurélien Max Kenji Yamada Xerox Research Centre Europe Grenoble CLIPS-GETA Université Joseph Fourier Grenoble Abstract This position paper argues for an interactive approach to text understanding. The proposed model extends an existing semantics-based text authoring system by using the input text as a source of information to assist the user in re-authoring its content. The approach permits a reliable deep semantic analysis by combining automatic information extraction with a minimal amount of human intervention. 1 Introduction Answering emails sent to a company by its customers to take just one example among many similar text-processing tasks requires a reliable understanding of the content of incoming messages. This understanding can currently only be done by humans and represents the main bottleneck to a complete automation of the processing chain other aspects could be delegated to such procedures as database requests and text generation. Current technology in natural language understanding or in information extraction is not at a stage where the understanding task can be accomplished reliably without human intervention. In this paper which aims at proposing a fresh outlook on the problem of text understanding rather than at describing a completed implementation we advocate an interactive approach where 1. The building of the semantic representation is under the control of a human author 2. In order to build the semantic representation the author interacts with an intuitive textual interface to that representation obtained from it through an NLG process where some active regions of the text are associated with menus that display a number of semantic choices for incrementing the representation 3. The raw input text to be analyzed serves as a source of information to the authoring system and permits to associate likelihood levels with the various authoring