Scientific Article Search System Based on Discourse Facet Representation
نویسندگان
چکیده
منابع مشابه
Automatic Identification of Discourse Moves in Scientific Article Introductions
This paper reports on the first stage of building an educational tool for international graduate students to improve their academic writing skills. Taking a text-categorization approach, we experimented with several models to automatically classify sentences in research article introductions into one of three rhetorical moves. The paper begins by situating the project within the larger framewor...
متن کاملScientific Article Summarization Using Citation-Context and Article's Discourse Structure
We propose a summarization approach for scientific articles which takes advantage of citation-context and the document discourse model. While citations have been previously used in generating scientific summaries, they lack the related context from the referenced article and therefore do not accurately reflect the article’s content. Our method overcomes the problem of inconsistency between the ...
متن کاملSWAN/SIOC: Aligning Scientific Discourse Representation and Social Semantics
SWAN/SIOC is an alignment of two Web ontologies that, taken together, represent Scientific Discourse in online communities at different levels of granularity (content items and discourse elements). The goal of this alignment is to make the discourse structure and component relationships much more accessible to computation, so that information can be navigated, compared and understood in a conte...
متن کاملFacet-based Exploratory Search in Topic Maps
In this contribution, we address exploratory search where a user is faced with an information need concerning a domain he lacks specific knowledge. Based on the work of Delbru et al., which introduced metrics to measure the navigational quality of automatically selected facets for RDF data, we apply those findings to the semantically richer TMDM and show how exploratory search functionality can...
متن کاملKnowledge Extraction Based on Discourse Representation Theory and Linguistic Frames
We have implemented a novel approach for robust ontology design from natural language texts by combining Discourse Representation Theory (DRT), linguistic frame semantics, and ontology design patterns. We show that DRT-based frame detection is feasible by conducting a comparative evaluation of our approach and existing tools. Furthermore, we define a mapping between DRT and RDF/OWL for the prod...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Proceedings of the AAAI Conference on Artificial Intelligence
سال: 2019
ISSN: 2374-3468,2159-5399
DOI: 10.1609/aaai.v33i01.33019859