Semantic impact graphs for information valuation

Sinan Al-Saffar, Gregory L. Heileman

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

5 Scopus citations

Abstract

Information valuation has typically been carried out implicitly in question-answering and document retrieval systems. We argue that explicit information valuation is needed to move away from the system and process-centric nature of implicit valuation which has also hindered the theoretical study of information value under a unified and explicit framework. In this paper we present a graphical-based model for explicit information valuation. Our model caters to the subjective nature of information quality by measuring the impact a candidate piece of information may have on a knowledge base representing the recipient's world view. Our model is capable of evaluating information semantically at the statement level and is in effect basing information- valuation on information-understanding. However, information value can be computed and predicted using our causal graph model without requiring full logical inference typically needed for information-understanding.

Original languageEnglish (US)
Title of host publicationDocEng'08 - Proceedings of the 8th ACM Symposium on Document Engineering
Pages209-212
Number of pages4
DOIs
StatePublished - 2008
Externally publishedYes
Event8th ACM Symposium on Document Engineering, DocEng 2008 - Sao Paulo, Brazil
Duration: Sep 16 2008Sep 19 2008

Publication series

NameDocEng'08 - Proceedings of the 8th ACM Symposium on Document Engineering

Conference

Conference8th ACM Symposium on Document Engineering, DocEng 2008
Country/TerritoryBrazil
CitySao Paulo
Period9/16/089/19/08

Keywords

  • Document ranking
  • Information valuation
  • Semantic Web search

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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