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Presentation at the "Reasoning from experiences on the Web" workshop (WebCBR 2010) at the International Conference on Case Based Reasoning 2010.Abstract:While Case-based reasoning (CBR) has successfully been deployed on the Web, its data models are typically inconsistent with existing information infrastructure and standards. In this paper, we examine how CBR can operate on the emerging Web of Data, with mutual benefits. The expense of knowledge engineering and curating a case base can be reduced by using Linked Data from the Web of Data. While Linked Data provides experiential data from many different domains, it also contains inconsistencies, missing data and noise which provide challenges for logic-based reasoning. CBR is well suited to provide alternative and robust reasoning approaches. We introduce (i) a lightweight CBR vocabulary which is suited for the open ecosystem of the emerging Web of Data, and provide (ii) a detailed example of a case base using data from multiple sources. We propose that for the first time the Web of Data provides data and a real context for open CBR systems.
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Chapter Copyright 2009 Digital Enterprise Research Institute. All rights reserved.
Digital Enterprise Research Institute www.deri.ie
Enabling Case-Based Reasoning on the Web of Data
(How to create a Web of Experience)
Benjamin Heitmann, Conor Hayes
Digital Enterprise Research Institute (DERI),National University of Ireland, Galway
Funded by Science Foundation Ireland under Grant No. SFI/08/CE/I1380 (Líon-2)
Digital Enterprise Research Institute www.deri.ie
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Motivation
characterisation of current CBR approaches: data storage is domain and use-case specific
no common data model
challenges: limited interoperability (“data silos”)
no reuse of cases or knowledge containers
data acquisition is expensive
the Web of Data can provide: 1. new sources of experiential data
2. standard way to publish and link experiential data
3. common data model for CBR interoperability
4. opportunity to establish CBR as a standard reasoning paradigm
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Digital Enterprise Research Institute www.deri.ie
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Overview:
1. related work in the CBR domain: existing approaches for CBR interoperability
2. introduction to the Web of Data: main concepts and principles
current sources for experiential data
3. applying the CBR methodology
to the Web of Data: lightweight CBR vocabulary
example and process for constructing a case base
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Digital Enterprise Research Institute www.deri.ie
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Related work: CBR interoperability
Case-Based Mark-Up Language (CBML), XML based: rigid CBR vocabulary, hard to customise for new domain.
hard to convert domain data, lack of real data.
CaseML (RDF based): rigid CBR vocabulary
requires a-priori knowledge of external sources
C-OWL (RDF based, extends OWL): formalisation of distributed reasoning for CBR using rules
common shortcomings: no reuse of domain semantics for cases no reuse by linking of case fragments
high overhead of transforming of external data into case data
4
Digital Enterprise Research Institute www.deri.ie
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Background: The Web of Data
the Web of Data provides: structured data, collaboratively
created, about object centred sociality domain knowledge through
ontologies (e.g. DBpedia ontology) cross-domain links between sources
Linked Data principles:
1. use URIs “for everything”
2. allow HTTP access to all URIs
3. when accessing a URI, provide relevant data in RDF
4. include links to URIs from third parties (background knowledge)
Linked Data can be very noisy, so CBR is well suited as a reasoning paradigm
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(a) July 2007 (b) April 2008 (c) Sep 2009 (d) July 2009
Digital Enterprise Research Institute www.deri.ie
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Sources of experiential data from the Web of Data
DBpedia provides cross-domain links
social web sites: Live Journal
MySpace
Facebook & Open Graph API
Yelp reviews
broadcasters & news: BBC program catalogue
New York Times subject headings
search engines providing access to this data: Google and Yahoo
Sindice
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example of structured data from Wikipedia, demonstrating the Linked Data principles
foaf:name
http://beck.com
"Beck"
foaf:homepage
dbpedia:Beck
Friend of a Friend (FOAF) vocabulary:
social relationships and information
dbpedia-owl:birthPlace dbpedia:Los_Angeles
DBPedia ontology
dbpprop:genre dbpedia:Anti-folk
DBPedia properties
skos:subject category:Anti-folk_musicians
Simple Knowledge Organisation System (SKOS): vocabulary for knowledge organisation
owl:sameAs fbase:Beck Web Ontology Language (OWL):links to identical resourcesopencyc:en/
Beck_MusicalPerformer
cbr:CaseBase
cbr:Case
cbr:Solution
cbr:has_casebase
cbr:has_solution
ex:UserProfiles
deri:Heitmann
amazon:RiverOfGods
myspace:Björk
cbr:has_casebase
foaf:interest
foaf:interest
rdf:type
rdf:type
CBR vocabularyExample CBR Case Base
Sources:DBPedia,
Amazon Reviews via Google RDFa,MySpace via DBTune
amazon:GravitysRainbow
myspace:BobDylan
foaf:interest
foaf:interest
cbr:has_casebase
deri:Hayes
Digital Enterprise Research Institute www.deri.ie
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CBR vocabulary for the Web of Data
modelling decisions: lightweight approach
intentional simplicity
reuse of existing domain semantics and vocabularies
flexible mapping of cases to entities
not fixed to domain or use case
focus on vocabulary and case knowledge
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Digital Enterprise Research Institute www.deri.ie
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Process for constructing a case base
Step 1: discovering and aggregating data use search engine or custom crawler to discover data
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Step 2: conversion of external data transform different RDF serialisations (RDFa, RDF/XML, XHTML) to cases in RDF
Step 3: authoring and curating of case base select relevant cases manually or automatically, via application logic
Digital Enterprise Research Institute www.deri.ie
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Summary: towards a Web of Experience
our simple example illustrates the future potential
towards a Web of Experience: publish experiential data in RDF
link it to the Web of Data
use cases: mining experiences from structured, user generated content.
open recommender systems
distributed CBR
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