TY - GEN
T1 - Dependency-based semantic parsing for concept-level text analysis
AU - Poria, Soujanya
AU - Agarwal, Basant
AU - Gelbukh, Alexander
AU - Hussain, Amir
AU - Howard, Newton
PY - 2014
Y1 - 2014
N2 - Concept-level text analysis is superior to word-level analysis as it preserves the semantics associated with multi-word expressions. It offers a better understanding of text and helps to significantly increase the accuracy of many text mining tasks. Concept extraction from text is a key step in concept-level text analysis. In this paper, we propose a ConceptNet-based semantic parser that deconstructs natural language text into concepts based on the dependency relation between clauses. Our approach is domain-independent and is able to extract concepts from heterogeneous text. Through this parsing technique, 92.21% accuracy was obtained on a dataset of 3,204 concepts. We also show experimental results on three different text analysis tasks, on which the proposed framework outperformed state-of-the-art parsing techniques.
AB - Concept-level text analysis is superior to word-level analysis as it preserves the semantics associated with multi-word expressions. It offers a better understanding of text and helps to significantly increase the accuracy of many text mining tasks. Concept extraction from text is a key step in concept-level text analysis. In this paper, we propose a ConceptNet-based semantic parser that deconstructs natural language text into concepts based on the dependency relation between clauses. Our approach is domain-independent and is able to extract concepts from heterogeneous text. Through this parsing technique, 92.21% accuracy was obtained on a dataset of 3,204 concepts. We also show experimental results on three different text analysis tasks, on which the proposed framework outperformed state-of-the-art parsing techniques.
UR - http://www.scopus.com/inward/record.url?scp=84958547489&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-54906-9_10
DO - 10.1007/978-3-642-54906-9_10
M3 - Contribución a la conferencia
SN - 9783642549052
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 113
EP - 127
BT - Computational Linguistics and Intelligent Text Processing - 15th International Conference, CICLing 2014, Proceedings
PB - Springer Verlag
T2 - 15th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2014
Y2 - 6 April 2014 through 12 April 2014
ER -