Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The detection of discourse structure of scientific documents is important for a number of tasks, including biocuration efforts, text summarisation, and the creation of improved formats for scientific publishing. Currently, many parallel efforts exist to detect a range of discourse elements at different levels of granularity, and for different purposes, including extraction of information from complex documents, alignment of parallel corpora across languages, and support for document summarization (particularly multi-document summarization). Another interesting class of applications comes from "bibliometrics" and "scientometrics". For example, for analysis of argument structure in full text articles from the scientific literature, it may be important to know where a particular reference is cited or where a particular statement is made (Background, Discussion, etc.). Another application might include tracking over time where (in what sections) an entity or concept is mentioned, to determine whether the mentions migrate from research claims into the "Background" or eventually to the "Methods" sections of articles, as the concept moves from "foreground" (subject of the research) to "background". In this panel  would like to, explore compare, contrast and evaluate different scientific discourse annotation schemes and tools, in order to ansr questions such as:   What motivates a certain level, method, viewpoint for annotating scientific text?   What is the annotation level for a unit of argumentation: an event, a sentence, a segment? What are advantages and disadvantages of all three?   How easily can different schemes to be applied to texts? Are they easily trainable?   Which schemes are most portable? Can they be applied to both full papers and abstracts? Can they be applied to texts in different domains?   How granular should annotation schemes be? What are the advantages/disadvantages of fine and coarse grained annotation categories?   What correlations occur among document structure, argumentation, and rhetorical functions?   Is there a common framework that could be used for domain-independent document structure annotation?
['Anita de Waard', 'Sophia Ananiadou', 'Maryann E. Martone', 'Ágnes Sándor', 'Hagit Shatkay']
I am writing a research paper on a idea Detecting and using document structure in scientific text
[{"from": "human", "value": "I am writing a research paper on a idea Detecting and using document structure in scientific text"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The detection of discourse structure of scientific documents is important for a number of tasks, including biocuration efforts, text summarisation, and the creation of improved formats for scientific publishing. Currently, many parallel efforts exist to detect a range of discourse elements at different levels of granularity, and for different purposes, including extraction of information from complex documents, alignment of parallel corpora across languages, and support for document summarization (particularly multi-document summarization). Another interesting class of applications comes from \"bibliometrics\" and \"scientometrics\". For example, for analysis of argument structure in full text articles from the scientific literature, it may be important to know where a particular reference is cited or where a particular statement is made (Background, Discussion, etc.). Another application might include tracking over time where (in what sections) an entity or concept is mentioned, to determine whether the mentions migrate from research claims into the \"Background\" or eventually to the \"Methods\" sections of articles, as the concept moves from \"foreground\" (subject of the research) to \"background\". In this panel  would like to, explore compare, contrast and evaluate different scientific discourse annotation schemes and tools, in order to ansr questions such as:   What motivates a certain level, method, viewpoint for annotating scientific text?   What is the annotation level for a unit of argumentation: an event, a sentence, a segment? What are advantages and disadvantages of all three?   How easily can different schemes to be applied to texts? Are they easily trainable?   Which schemes are most portable? Can they be applied to both full papers and abstracts? Can they be applied to texts in different domains?   How granular should annotation schemes be? What are the advantages/disadvantages of fine and coarse grained annotation categories?   What correlations occur among document structure, argumentation, and rhetorical functions?   Is there a common framework that could be used for domain-independent document structure annotation?"}]