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Title:
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Multi-level mining and visualization of scientific text collections
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Author:
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Accuosto, Pablo; Ronzano, Francesco; Ferrés, Daniel; Saggion, Horacio
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Abstract:
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Comunicació presentada a: 6th International Workshop on Mining Scientific Publications (WOSP 2017), celebrat el 19 de juny a Toronto, Canada. |
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Abstract:
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We present a system to mine and visualize collections of scientific
documents by semantically browsing information extracted
from single publications or aggregated throughout corpora of articles.
The text mining tool performs deep analysis of document
collections allowing the extraction and interpretation of research
paper’s contents. In addition to the extraction and enrichment of
documents with metadata (titles, authors, affiliations, etc), the deep
analysis performed comprises semantic interpretation, rhetorical
analysis of sentences, triple-based information extraction, and text
summarization. The visualization components allow geographicalbased
exploration of collections, topic-evolution interpretation, and
collaborative network analysis among others. The paper presents a
case study of a bilingual collection in the field of Natural Language
Processing (NLP). |
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Abstract:
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This work is (partly) supported by the Spanish Ministry of Economy
and Competitiveness under the Maria de Maeztu Units of Excellence
Programme (MDM-2015-0502) and by the TUNER project (TIN2015-
65308-C5-5-R, MINECO/FEDER, UE). |
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Subject(s):
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-Language Resources
-Scientific Text Mining
-Information Extraction
-Data Visualization
-PDF Conversion
-Big Scientific Data |
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Rights:
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© 2017 Association for Computing Machinery
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Document type:
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Conference Object
Article - Accepted version |
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Published by:
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ACM Association for Computer Machinery
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