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2020 | OriginalPaper | Buchkapitel

Interactive Text Graph Mining with a Prolog-based Dialog Engine

verfasst von : Paul Tarau, Eduardo Blanco

Erschienen in: Practical Aspects of Declarative Languages

Verlag: Springer International Publishing

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Abstract

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.

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Nächstes Kapitel Flexible Graph Matching and Graph Edit Distance Using Answer Set Programming
Fußnoten
1
Our implementation is available at https://​github.​com/​ptarau/​DeepRank.
 
2
A lemma is a canonical representation of a word, as it stands in a dictionary, for all its inflections e.g., it is “be” for “is”, “are”, “was” etc.
 
5
More general and, respectively, more specific concepts.
 
6
Concepts corresponding to objects that are part of, and, respectively, have as part other objects.
 
10
And also speak them out if the quiet flag is off.
 
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Metadaten
Titel
Interactive Text Graph Mining with a Prolog-based Dialog Engine
verfasst von
Paul Tarau
Eduardo Blanco
Copyright-Jahr
2020
Buch
Practical Aspects of Declarative Languages

Print ISBN: 978-3-030-39196-6

Electronic ISBN: 978-3-030-39197-3

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-3-030-39197-3_1