A demonstration of Sya: A spatial probabilistic knowledge base construction system

Ibrahim Sabek, Mashaal Musleh, Mohamed Mokbel

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

3 Citations (Scopus)

Abstract

This demo presents Sya; the first full-fledged spatial probabilistic knowledge base construction system. Sya is a comprehensive extension to the DeepDive [18] system that enables exploiting the spatial relationships between extracted relations during the knowledge base construction process, and hence results in a better knowledge base output. Sya runs existing DeepDive programs as is, yet, it extracts more accurate relations than DeepDive when dealing with input data that have spatial attributes. Sya employs a simple spatial high-level language, a rule-based spatial SQL query engine, a spatially-indexed probabilistic graphical model, and an adapted spatial statistical inference technique to infer the factual scores of relations. We demonstrate a system prototype of Sya, showing a case study of constructing a crime knowledge base. The demonstration shows to the audience the internal steps of building the knowledge base, as well as a comparison with the output of DeepDive.

Original languageEnglish
Title of host publicationSIGMOD 2018 - Proceedings of the 2018 International Conference on Management of Data
PublisherAssociation for Computing Machinery
Pages1689-1692
Number of pages4
ISBN (Electronic)9781450317436
DOIs
Publication statusPublished - 27 May 2018
Event44th ACM SIGMOD International Conference on Management of Data, SIGMOD 2018 - Houston, United States
Duration: 10 Jun 201815 Jun 2018

Other

Other44th ACM SIGMOD International Conference on Management of Data, SIGMOD 2018
CountryUnited States
CityHouston
Period10/6/1815/6/18

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Keywords

  • Knowledge base construction
  • Spatial knowledge bases

ASJC Scopus subject areas

  • Software
  • Information Systems

Cite this

Sabek, I., Musleh, M., & Mokbel, M. (2018). A demonstration of Sya: A spatial probabilistic knowledge base construction system. In SIGMOD 2018 - Proceedings of the 2018 International Conference on Management of Data (pp. 1689-1692). Association for Computing Machinery. https://doi.org/10.1145/3183713.3193558