on the Semantic Web

religiondressInternet and Web Development

Oct 21, 2013 (3 years and 9 months ago)

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Tom Heath

Enrico Motta

Knowledge Media Institute

The Open University


12/06/2006

Personalizing Relevance

on the Semantic Web

through Trusted Recommendations
from a Social Network

Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

2

search results,

personalised to you

Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

3

overview


a traditional approach to personalisation


re
-
defining relevance


our approach (work in progress)


personalising relevance in information seeking


recommendations from people we trust


semantic web as deployment platform


Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

4

personalisation: a traditional
approach

Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

5

Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

6

personalisation: a traditional
approach


operates in a closed world


the task supported is poorly defined


Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

7

can we personalise a very

specific task?

Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

8

Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

9


irrelevant to the topic


irrelevant to me

Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

10

the nature of relevance



topical relevance:
query


pages



personal relevance:
my info need
↔ items

Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

11

a system for personalised
relevance

Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

12

“known person recommendation”


ask people I know and trust


source
-
centric


allows for more complex reasoning


knowledge required


who is known?


what’s the task/situation?



who is most trusted?

Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

13

who is most trusted, and why?

…it depends on



five trust factors


expertise, experience, impartiality, affinity, track
record


the nature of the task


how critical the task, how subjective the solution



(Heath, Motta and Petre, 2006)

Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

14

implementation

Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

15

a system for personalised
relevance


domain:
travel/tourism


non
-
critical, highly subjective


significant trust factors


affinity

between the info seeker and info source


experience

of each person of particular domains


data requirements


who do you know? (FOAF)


how trustworthy are they?


a pool of potential results

Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

16

system components


reviewing/rating system, for “travel objects”


provides pool of potential results


outputs RDF/XML according to Review vocab


trust kb, computes trust relationships:


affinity


experience


search system


search index


relevance reasoner

Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

17

workflow

1.
users provide FOAF files and ratings of travel
things

2.
system infers trust relationships

3.
rated travel things are added to search index

4.
user does keyword search

5.
search system looks for results rated by known
people

6.
relevance reasoner ranks results based on
inferred trustworthiness of the source

Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

18

future work


complete the implementation


evaluate the importance of affinity vs
experience in trust inferences


evaluate the relevance of search these
personalised

results


Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

19

thankyou

Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

20

t.heath@open.ac.uk


http://kmi.open.ac.uk/people/tom

Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

21


Personalizing Relevance on the Semantic Web

Tom Heath and Enrico Motta, KMi, The Open University

12/06/2006

22

Trust

KB


Semantic
Descriptions of
Travel Things

Reviews

of Travel
Things

Social
Network
Definition

Search and
Ranking
Logic

Search
Index


Review/

Rating
System

PHP/RAP/MySQL

Web sites of
Travel Things
(Hotels, Sights…)

(X)HTML

RDF/XML

Reviews Ontology


Jena

Lucene

Java

Search and
Results Interface

RDF/XML

FOAF Ontology


RDF/XML

Travel Things Ontology


Semantic
Description Miner

GRDDL? Armadillo?

Text Garden?


Results

Task
Characteristics