TY - GEN
T1 - Interactive Text Graph Mining with a Prolog-based Dialog Engine
AU - Tarau, Paul
AU - Blanco, Eduardo
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - On top of a neural network-based dependency parser and a graph-based natural language processing module we design a Prolog-based dialog engine that explores interactively a ranked fact database extracted from a text document. We reorganize dependency graphs to focus on the most relevant content elements of a sentence, integrate sentence identifiers as graph nodes and after ranking the graph we take advantage of the implicit semantic information that dependency links bring in the form of subject-verb-object, “is-a” and “part-of” relations. Working on the Prolog facts and their inferred consequences, the dialog engine specializes the text graph with respect to a query and reveals interactively the document’s most relevant content elements. The open-source code of the integrated system is available at https://github.com/ptarau/DeepRank.
AB - On top of a neural network-based dependency parser and a graph-based natural language processing module we design a Prolog-based dialog engine that explores interactively a ranked fact database extracted from a text document. We reorganize dependency graphs to focus on the most relevant content elements of a sentence, integrate sentence identifiers as graph nodes and after ranking the graph we take advantage of the implicit semantic information that dependency links bring in the form of subject-verb-object, “is-a” and “part-of” relations. Working on the Prolog facts and their inferred consequences, the dialog engine specializes the text graph with respect to a query and reveals interactively the document’s most relevant content elements. The open-source code of the integrated system is available at https://github.com/ptarau/DeepRank.
KW - Dependency graphs
KW - Graph-based natural language processing
KW - Logic-based dialog engine
KW - Synergies between neural and symbolic text processing
KW - query-driven salient sentence extraction
UR - http://www.scopus.com/inward/record.url?scp=85079085447&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85079085447&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-39197-3_1
DO - 10.1007/978-3-030-39197-3_1
M3 - Conference contribution
AN - SCOPUS:85079085447
SN - 9783030391966
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 3
EP - 19
BT - Practical Aspects of Declarative Languages - 22nd International Symposium, PADL 2020, Proceedings
A2 - Komendantskaya, Ekaterina
A2 - Liu, Yanhong Annie
PB - Springer
T2 - 22nd International Symposium on Practical Aspects of Declarative Languages, PADL 2020
Y2 - 20 January 2020 through 21 January 2020
ER -