Knowledge Driven Intelligent Survey Systems for Linguists

Ricardo Soares, Elspeth Edelstein, Jeff Z. Pan, Adam Wyner

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose Knowledge Graph (KG), an articulated underlying semantic structure, to be a semantic bridge between human and systems. To illustrate our proposal, we focus on KG based intelligent survey systems. In state of the art systems, knowledge is hard-coded or implicit in these systems, making it hard for researchers to reuse, customise, link, or transmit the structured knowledge. Furthermore, such systems do not facilitate dynamic interaction based on the semantic structure. We design and implement a knowledge-driven intelligent survey system which is based on knowledge graph, a widely used technology that facilitates sharing and querying hypotheses, survey content, results, and analyses. The approach is developed, implemented, and tested in the field of Linguistics. Syntacticians and morphologists develop theories of grammar of natural languages. To evaluate theories, they seek intuitive grammaticality (well-formedness) judgments from native speakers, which either support a theory or provide counter-evidence. Our preliminary experiments show that a knowledge graph based linguistic survey can provide more nuanced results than traditional document-based grammaticality judgment surveys by allowing for tagging and manipulation of specific linguistic variables.supports very fast parallel bit computation. As a semantic compression method for structured data, besides the reduction of syntactic verbosity and data redundancy, we also invoke semantics in the RDF datasets. Experiments on various datasets show competitive results in terms of compression ratio.
Original languageEnglish
Title of host publicationSemantic Technology
Subtitle of host publication8th Joint International Conference, JIST 2018, Awaji, Japan, November 26–28, 2018, Proceedings
EditorsRyutaro Ichise, Freddy Lecue, Takahiro Kawamura, Dongyan Zhao, Stephen Muggleton, Kouji Kozaki
Place of PublicationCham
PublisherSpringer International Publishing
Pages3-18
Number of pages16
ISBN (Electronic)978-3-030-04284-4
ISBN (Print)978-3-030-04283-7
DOIs
Publication statusPublished - 14 Nov 2018
EventThe 8th Joint International Semantic Technology Conference - Awaji City, Japan
Duration: 26 Nov 201828 Nov 2018
http://jist2018.knowledge-graph.jp/

Publication series

NameLecture Notes in Computer Science
PublisherSpringer, Cham
Volume11341
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceThe 8th Joint International Semantic Technology Conference
Abbreviated titleJIST 2018
CountryJapan
CityAwaji City
Period26/11/1828/11/18
Internet address

Keywords

  • Knowledge graph
  • Intelligent survey system
  • Grammaticality judgments

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