Reporton

ACM SIGIR Workshop on “Semantic Web”
SWIR 2003
Toronto, Canada
August 1, 2003
Ying Ding#, Cornelis J. van Rijsbergen*, Iadh Ounis*, Joemon Jose*#University of Innsbruck, Austria*
University of Glasgow, UK

1. Introduction
This was the first workshop combining semantic web and information retrieval (IR). So far, thetwo communities were working independently, whereas they address more or less commonissues. The main aim of the workshop was to bring together these two disparate communities.
The workshop has been subsidized by the OntoWeb Consortium (www.ontoweb.org, EU
Thematic Network on Semantic Web). We have received 15 papers in total. We had experts
representing both the semantic web and the IR fields as reviewers. All the submitted papers werethoroughly reviewed by at least 4 people representing both fields. Based on these reviews, weselected 7 very good papers dealing with various aspects of both information retrieval andsemantic web. In addition, we scheduled two invited talks, spanning two important aspects of thesemantic web. Dr Arturo Trujillo, of the Canon Research Centre Europe Ltd, has kindly chairedthe workshop. The workshop attracted an audience of more than 30 people, who were encouraged
to interact with the authors and the invited speakers.

2. Purpose & Motivation
The emergence of the Internet has brewed the revolution of information storage and retrieval.
Tons of web pages are being appended to the Internet on a daily basis, and this causes to explodethe amount of available information on the Web dramatically. These dynamic data strongly
hinder the efficiency and the effectiveness of current searching facilities. Although variousindexing, cataloguing and search systems are easily accessible from the web, their functions toretrieve relevant information and manage knowledge are still very limited. Therefore, effective orintelligent search for information on this massive information resource becomes highly critical.
Tim Berners-Lee created the vision of a semantic web that enables automated information accessand use, based on machine-processable semantics of data. In his informal ‘Semantic Web Road1

Map’ note1, he outlined possible future directions for the evolution of the World Wide Web.
These ideas have been met with growing enthusiasm of researchers and developers world-wide,both in academia and in industry. They encourage the integration of ongoing efforts fromdifferent disciplines, involving specialists in Information Retrieval, Natural Language Processing,Information Extraction, Knowledge Representation, Artificial Intelligence and Databases. Theseefforts aim at capturing the semantics of digital content of all sorts and origins, and making
current Web to be easily accessed and precisely retrieved.
Information retrieval can benefit from building ontologies and other semantic structures, making
it possible to have a better understanding of the application domains and the user queries. Indeed,semantic web technologies could be a basis for intelligent retrieval. On the other hand, theinformation retrieval field has a lot to bring to the semantic web community, based on the 30years of research and development in the context of very large collections of documents. This
workshop aimed to bring researchers from the two communities together.

3. Background Information on Semantic Web
The web was initially designed for direct human processing. With its current structure, machinebased approaches to web applications are not possible unless its content is transformed into amachine-readable format encoding semantic information. Ontologies are the backbone
technology for the semantic web and - more generally - for the management of formalized
knowledge within the technical context of distributed systems. They provide machine-processable
semantics of data and information sources that can be communicated between different agents(software and people).
The semantic web has to go beyond the simple bag-of-words approach currently used by searchengines and get closer to the meaning of the texts. One of the most important things missing incurrent web technologies is a link between the texts and external lexical resources encoding
semantic information. The following common problems can be easily foreseen in conventional
keyword-based information retrieval systems:• Searching information: Existing keyword-based search retrieves irrelevant information due
to term ambiguity, and misses information when material related to similar concepts is stored
under quite different terms.
• Extracting information: Currently, people have to browse and read extensively in order toextract relevant information from textual or other representations. Software agents do notpossess the common-sense knowledge required to assist effectively in tasks of this type, letalone automate them. Moreover, they fail to integrate information from different sources.
• Maintaining large repositories of weakly structured text is a difficult and time-consuming
activity.
• Adaptation and dynamic reconfiguration of information repositories (e.g. websites)
according to user profiles or other aspects of relevance, hinges on automatic document
generation and is not yet fully mastered.
Ontologies that provide shared, common domain theories will be a key enabler to tackle theseproblems. Ontologies can be regarded as metadata that explicitly represent the semantics of data1

http://www.w3.org/DesignIssues/Semantic.html

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for machine processing. Once the data on the web is understandable and represented in amachine-processable format, further information, not necessarily explicit in the text, can begathered via ontologies. This would provide the basis for extracting information, reasoning
around the stored data, answering questions, and other applications. By making explicit the link
between the form and the content of information, ontologies help people and computers accessthe information they need, and effectively communicate with each other. They have a crucial rolein enabling content-based access, interoperability, and communication across the web.
Semantic web technologies and especially the use of ontologies, are expected to enable a muchhigher degree of automation and scalability in performing operations pertaining to the above
mentioned tasks. For instance, in order to keep weakly structured collections consistent, or togenerate information presentations from semi-structured data, the semantics of these collections
and data must not only be machine-accessible but also machine-processable. In other words, thesemantics must be represented based on formal ontologies.
Semantic web will provide intelligent access to heterogeneous, distributed information, enabling
software products to mediate between user needs and the information sources available. Web
services can be accessed and executed via the web. However, all these service descriptions arebased on semi-formal natural language descriptions. Therefore, the human programmer needs tobe kept in the loop and the scalability as well as economy of web services are limited. Bringing
them to their full potential requires their combination with semantic web technology. This
technology will provide mechanization in service identification, configuration, comparison andcombination. Semantic web enabled web services have the potential to change our life to a muchhigher degree than the current web already has. Semantic retrieval to support web services willbe the promising vision in the foreseeable future.
4. Topics
Topics of this workshop are centred on semantic web and information retrieval and how to
combine both in order to achieve mutual benefit and high impact. The workshop aimed to address
the following areas: Ontology-based Information Retrieval or Semantic Information Retrieval;
Metadata in Information Retrieval; Ontology Learning based on Information Extraction andNatural Language Processing Technologies; Automatic Indexing and Cataloguing; Information
Retrieval and Web Services; Languages, Tools and Methodologies for Semantic Annotations;
Knowledge Portals; Semantic Web Mining; Semantic Web Searching and Querying; Semantic
Web for Multimedia Retrieval; Semantic Web for Multilingual Information Retrieval; Semantic
Web for Digital Library; Semantic Interoperability and Integration; Semantic Web and Peer-toPeer; Semantic Web for Information Visualization; Peer-to-Peer for Information Retrieval; UserStudies for Semantic Web; Business Applications and Best of Practice.
5. Presentation Summaries
As mentioned in the introduction, the event included the schedule of two invited talks:- A talk by Atanas Kiryakov from OntoText, Bulgaria. OntoText is a company that has
successfully combined natural language processing with semantic web technologies. Atnas
Kiryakov gave a talk on Semantic indexing and retrieval. He presented a vision about a holisticsystem allowing annotation, indexing, and retrieval of documents with respect to real-world
entities. An operational system based on this, called KIM, has been developed. KIM shows thepossibility to enhance current information extraction and information retrieval system by using
semantic web technologies.

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- Dr Christoph Bussler from Digital Enterprise Research Institute (DERI), National University ofIreland, Galway, is the renowned expert in the semantic web services area. He gave a contribution
on message mediation in composite web services. Web services powered by semantic web
technology are the pioneering and challenging applications in the semantic web area. This
contribution was meant to introduce us to this trendy application.
Furthermore, the event included the presentation of the following 7 papers:
J. Mayfield and T. Finin (The Johns Hopkins University, University of Maryland, USA):
Information Retrieval on the Semantic Web: Integrating inference and retrieval.
The authors discussed some very interesting issues regarding the combination of information
retrieval techniques with current semantic web technologies. In a nutshell, the authors aim toadopt the inference mechanism currently used in semantic web field to information retrieval, inorder to improve retrieval performance.
A. Ankolekar, Y.W. Seo and K. Sycara (Carnegie Mellon University, USA): Investigating
Semantic Knowledge for Text Learning
The authors explore the hypothesis that the use of an ontology can be useful to extract features
for document clustering. They compared two methods of statistical feature extraction against
manually created ontologies for a text classification task. Their experiments on a standard text
collection (Reuters-21578 database), considered as a reference in the domain of textclassification, show a limited advantage of ontology-based classification as compared to standard
approaches.
A. Hotho, S. Staab and G. Stumme (University of Karlsruhe, Germany): Wordnet improves Text
Document Clustering
Hotho and al. investigate and evaluate different strategies for using ontological information,
derived from WordNet, to supplement document-clustering algorithms. It is shown how the
representation of documents is enriched to incorporate related concepts obtained from WordNet.
These representations are then used to form cluster of documents by means of a variant of theKMeans clustering algorithm. Various ways of using the information from WordNet for
document expansion are evaluated. The outcome of the experiments shows some promising
improvements from the use of such expressive representations.
C. Ciorascu, I. Ciorascu and K. Stoffel (Université de Neuchâtel, Switzerland): KnowlerOntological Support for Information Retrieval
The authors presented an information retrieval system, which allows complex queries that
require searches through WordNet. It proposes the use of the ontology language (OWL) forinterchanging semantic information in large-scale IR systems. The authors have built an OWL
ontology, which includes knowledge from Wordnet, stemming information and a whole
document base. Experiments on time-performance access to the ontology are reported. Theevaluation shows that a very good scalability is achieved by using persistency at both storage andreasoning levels.

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P.H. Meland, J. Austvik and J. Heggland (Norwegian University of Science and Technology,Norway): Using Ontologies and Semantic Networks with Temporal MediaThe authors discussed the annotation of video and audio data, describing a system forannotating and retrieving such data based on RDF ontologies. The most recent standards andapproaches related to both multimedia and semantic web knowledge representation are properlyintroduced and discussed. Authors show how their system integrates and uses this knowledge.

J. Klavans, S.D. Popper and R. Passonneau (Columbia University, USA): Tackling the Internet
Glossary Glut: Automatic Extraction and Evaluation of Genus Phrases
This work discussed the automatic evaluation of a method for extraction of term definitions,based on a gold standard created through human annotation of test data. The authors briefly
described a natural language processing system that extracts genus phrases from Internet
documents. The method has immediate applications in the automatic construction of thesauri,
dictionaries and ontologies. Furthermore, the authors discuss a few insights in the problems
entailed by the development of a gold standard for genus phrases.

C. Brewster, F. Ciravegna and Y. Wilks (University of Sheffield, UK): Background andForeground Knowledge in Dynamic Ontology Construction: Viewing Text as Knowledge
Maintenance
The authors identified important issues around the topic of learning ontologies/taxonomies
from document sets. They provided a nice introduction regarding the relations between text,
backgound and foreground knowledge. Within this framework they present and discuss a possible
approach for ontology extraction from text, supported by external - richer and better-structured sources of knowledge. In particular, authors discussed several issues regarding the(im)possibilities of identifying background knowledge. This contribution was backed up by aninteresting, informal testing (correctly identified by the authors).

6. Conclusions
This workshop was a pleasant experience with the participation of people from two different
research fields. The fusion of these communities sparked off strong intellectual debate andinteractions. This encouraged participants to continue their research addressing both the topics.
We believe there was a strong interest in this SWIR 2003 workshop particularly given the adverse
circumstances prevalent at the time of paper submission. This suggests there is a case forcontinuous effort along these lines.

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