This document discusses Benjamin Heitmann's research interests which include distributed architectures for recommendations on the Web of Data. It provides background on Heitmann and outlines some of his recent work identifying common components of Semantic Web applications. Finally, it contrasts current recommender systems with Heitmann's vision of future distributed recommender architectures that can provide recommendations across multiple linked data sources and domains.

1. Digital Enterprise Research Institute www.deri.ie
Distributed architecture for
recommendations on the Web of Data
Benjamin Heitmann
 Copyright 2009 Digital Enterprise Research Institute. All rights reserved.
Chapter

2. About me
Digital Enterprise Research Institute www.deri.ie
 PhD student at Digital Enterprise Research Institute,
National University of Ireland, Galway:
“Distributed architecture for knowledge discovery in
linked data”
 computer science master from University of
Karlsruhe, Germany: Transitioning web application
frameworks towards the Semantic Web (2008)
 Philosophy was a minor subject for my masters
(information ethics, political philosophy)
 28 years old, German citizen, born in Switzerland,
grew up in south Germany (Baden-Württemberg, the
part of the South which is not Bavaria :)
Benjamin Heitmann

3. Research interests:
Digital Enterprise Research Institute www.deri.ie
 the architecture of the Web, the Semantic Web
and the Web of Data
 the influence of these architectures on the ability
to provide recommendations
 identifying and creating best practices and
guidelines for enabling recommendations on the
Web of Data
 engineering solutions like software components
and frameworks to provide recommendations on
the Web of Data
 understanding interplay between social uptake of
standards and architecture of the Web of Data
Benjamin Heitmann

4. Recent work: identifying common
components of Semantic Web applications
Digital Enterprise Research Institute www.deri.ie
Authoring
User interface
Interface
(92%) Search
(32%)
Service
(81%)
Data Interface
Integration (100%)
Service
(72%) Persistent Remote
Crawler
Storage Data
(35%)
(91%) Sources
from: Heitmann, B., et al., “Towards a reference architecture for
Semantic Web applications,” Proceedings of the 1st Int. Web
Science Conference, 2009
Benjamin Heitmann

5. Common components of a Semantic Web
application
Digital Enterprise Research Institute www.deri.ie
 Data Interface (100%): Abstraction layer regarding
implementation, number &distribution of persistence layers.
 Persistent Storage (91%): Persistent storage of data and run
time state.
 User Interface (92%): Human accessible interface for using
application and viewing data. (“read-only”)
 Authoring Interface (32%): Edit, create, import or export
data.
 Integration Service (72%): Merge Structure, Syntax or
Semantics of data from multiple heterogeneous sources.
 Search Service (81%): Search on content + semantic features.
 Crawler (35%): Retrieval of remote data for integration
service.
Benjamin Heitmann

6. State of the art: recommender systems
Digital Enterprise Research Institute www.deri.ie
 Problem: to much data to
be viewed by humans.
Application logic
 Pre-selection necessary!
 current recommender
Recommendation
algorithm
systems:
 one data source with one
data model
Data source  one recommendation
algorithm
 system fine-tuned for one
closed system, e.g. fixed domain (e.g. books)
Amazon book recommendation  closed, internal system
Benjamin Heitmann

7. Future research: distributed architecture for
recommendations on the Web of Data
Digital Enterprise Research Institute www.deri.ie
 distributed
Application logic
recommender systems:
 multiple data sources
Recommendation
algorithm  portable across domains
Data integration
 using linked data
 Challenges:
 identify stake-holders
Data providing
Data
integration
 which algorithms are
application
provider suited for such
Data
recommendations?
Data
source 1
Data
source 2
source 3  How do architecture and
algorithm influence each
other?
Benjamin Heitmann