| PID |
Title |
Authors |
Abstract |
| 5 |
Semantic Telecommunications Network Capability Services |
- Xiuquan Qiao*, BUPT
- Xiaofeng Li, BUPT
|
The providing of pervasive services in the B3G/4G network presents a great
challenge in light of well known problems like context-awareness, semantic
service description, accurate service query and dynamic service composition.
To eliminate the semantic gap of Telecommunications Network and Internet
in the service layer, we propose the semantic Telecommunications Network
Capability Services (TNCS). By comparing the differences between TNCS and
the plain web services, we present a semantic description approach for TNCS
by extending OWL-S. Then using this approach, we demonstrate a service profile
description case for semantic Parlay X. In this way, the ontology-based
accurate query, matching, automatic composition and invocation for telecommunication
network capability services can be supported. This will facilitate the semantic
convergence of telecommunications network and Internet in the service layer. |
| 12 |
Integrating Lightweight Reasoning into Class-Based Query Refinement for
Object Search |
- Gong Cheng*, Southeast University
- Yuzhong Qu, SouthEast University, China
|
More and more RDF data have been published online to be consumed. Ordinary
Web users also expect to experience more intelligent services promised by
the Semantic Web, such as object search based on structured data. We implemented
the Falcons search engine to meet the challenge. To enable keyword search,
for each object, we construct and index a virtual document that includes
textual descriptions of its neighboring resources. Typing information is
used to serve class-based query refinement, and lightweight reasoning is
performed to discover implicit types of objects. A method of recommending
subclasses is implemented to enable navigating class hierarchies for incremental
query refinement. We also report on lessons learned from Web-scale experiments. |
| 14 |
A Modularization-based Approach to Finding All Justifications for OWL
DL Entailments |
- Boontawee Suntisrivaraporn*, TU Dresden
- Guilin Qi, University of Karlsruhe
- Qiu Ji, University of Karlsruhe
- Peter Haase, University of Karlsruhe
|
Finding the justifications for an entailment (i.e., minimal sets of axioms
responsible for it) is a prominent reasoning service in ontology engineering,
as justifications facilitate important tasks like debugging inconsistencies
or undesired subsumption. Though several algorithms for finding all justifications
exist, issues concerning efficiency and scalability remain a challenge due
to the sheer size of real-life ontologies. In this paper, we propose a novel
method for finding all justifications in OWL DL ontologies by limiting the
search space to smaller modules. To this end, we show that so-called locality-based
modules cover all axioms in the justifications. We present empirical results
that demonstrate an improvement of several orders of magnitude in the efficiency
and scalability of finding all justifications in OWL DL ontologies. |
| 21 |
DL-Lite with role inclusions |
- Roman Kontchakov*, Birkbeck College, London
- Michael Zakharyaschev, Birkbeck College, London
|
We analyse DL-Lite logics with role inclusions and present a complete
classification of the trade-off between their expressiveness and computational
complexity. In particular, we show that in logics with role inclusions the
data complexity of instance checking becomes P-hard in the presence of functionality
constraints, and coNP-hard if arbitrary number restrictions are allowed,
even with a very primitive form of concept inclusions. Moreover, the combined
complexity of satisfiability in this case jumps to ExpTime. On the positive
side, it turns out that the combined complexity for the logics without number
restrictions depends only on the form of concept inclusions and can range
from NLogSpace and P to NP; the data complexity for such logics stays in
LogSpace. |
| 22 |
Catriple: Extracting Triples from Wikipedia Categories |
- Qiaoling Liu*, Shanghai Jiao Tong University
- Kaifeng Xu, Shanghai Jiao Tong University
- Lei Zhang, IBM China Research Lab Haofen Wang, Shanghai Jiao Tong
University
- Yong Yu, Shanghai Jiao Tong University
- Yue Pan, IBM Research Lab, China
|
As an important step towards bootstrapping the Semantic Web, many efforts
have been made to extract triples from Wikipedia because of its wide coverage,
good organization and rich knowledge. One kind of important triples is about
Wikipedia articles and their non-isa properties, e.g. (Beijing, country,
China). Previous work has tried to extract such triples from Wikipedia infoboxes,
article text and categories. The infobox-based and text-based extraction
methods depend on the infoboxes and suffer from a low article coverage.
In contrast, the category-based extraction methods exploit the widespread
categories. However, they rely on predefined relations and specific regular
expressions, which is too effort-consuming and explores only very limited
knowledge in the categories. This paper automatically extracts triples from
the less explored Wikipedia categories so as to achieve a wider article
coverage with less manual effort. We manage to realize this goal by utilizing
the syntax and semantics brought by super-sub category pairs in Wikipedia.
Our prototype implementation outputs about 10M triples with a 12-level confidence
ranging from 47.0\% to 96.4\%, which cover 78.2\% of Wikipedia articles.
Among them, 1.27M triples have confidence of 96.4\%. Applications can on
demand use the triples with suitable confidence. |
| 28 |
Semantically Conceptualizing and Annotating Tables |
- David Embley*, Brigham Young University
- Stephen Lynn, Brigham Young University
|
Enabling a system to automatically conceptualize and annotate a human-readable
table is one way to create interesting semantic-web content. But exactly
“how?” is not clear. With conceptualization and annotation in
mind, we investigate a semantic-enrichment procedure as a way to turn syntactically
observed table layout into semantically coherent ontological concepts, relationships,
and constraints. Our semantic-enrichment procedure shows how to make use
of auxiliary world knowledge to construct rich ontological structures and
to populate these ontological structures with instance data. The system
uses auxiliary knowledge (1) to recognize concepts and which data values
belong to which concepts, (2) to discover relationships among concepts and
which data-value combinations represent relationship instances, and (3)
to discover constraints over the concepts and relationships that the data
values and data-value combinations should satisfy. Experimental evaluations
indicate that the automatic conceptualization and annotation processes perform
well, yielding F-measures of 90% for concept recognition, 77% for relationship
discovery, and 90% for constraint discovery in web tables selected from
the geopolitical domain. |
| 29 |
Snippet Generation for Semantic Web Search Engines |
- Thomas PENIN*, Shanghai Jiao Tong University
- Haofen Wang, Shanghai Jiao Tong University
- Thanh Tran, Institute AIFB, University Karlsruhe
- Yong Yu, Shanghai Jiao Tong University
|
With the development of the Semantic Web, more and more ontologies are
available for exploitation by semantic search engines. However, while semantic
search engines support the retrieval of candidate ontologies, the final
selection of the most appropriate ontology is still difficult for the end
users. In this paper, we extend existing work on ontology summarization
to support the presentation of ontology snippets. The proposed solution
leverages a new semantic similarity measure to generate snippets that are
based on the given query. Experimental results have shown the potential
of our solution in this problem domain that is largely unexplored so far. |
| 32 |
The Art of Tagging: Measuring the Quality of Tags |
- Ralf Krestel*, Research Center L3S
- Ling Chen, Research Center L3S
|
Collaborative tagging, supported by many social networking websites, is
currently enjoying an increasing popularity. The usefulness of this largely
available tag data has been explored in many applications including emergent
semantics deriving, web resources categorization, and web search etc. However,
since tags are supplied by users freely, not all of them are useful and
reliable, especially when they are generated by spammers with malicious
intent. Identifying tags of high quality, therefore, is critical in improving
the performance of applications based on tags. In this paper, we propose
TRP-Rank (Tag-Resource Pair Rank), an algorithm to measure the quality of
tags by employing a quality propagating technique. The three dimensional
relationship among users, tags and web resources is firstly represented
by a graph structure. A set of seed nodes, where each node represents a
tag annotating a resource, are then selected and their quality is assessed.
The quality of the remaining nodes is calculated by propagating the known
quality of the seeds through the graph structure. We evaluate our approach
on a public data set where bad tags generated by suspicious spammers are
manually labelled. The experimental results demonstrate the effectiveness
of this approach in measuring the quality of tags. |
| 38 |
An Integrated Approach for Automatic Construction of Bilingual Chinese-English
WordNet |
- Renjie Xu*, Southeast University
- Zhiqiang Gao, Southeast University
- Yingji Pan, Southeast University
- Yuzhong Qu, SouthEast University, China
- Zhisheng Huang, Vrije Universiteit Amsterdam
|
This paper compares various approaches for constructing Chinese-English
bilingual WordNet. First, we implement three independent approaches that
translate English WordNet to Chinese WordNet automatically, including Minimum
Distance (MDA), Intersection (IA) and Words Co-occurrence (WCA). Minimum
Distance compares the gloss of synset with the explanations of words from
dictionaries. Intersection chooses the intersection part of Chinese in a
synset. Words Co-occurrence counts the results of Chinese and English words
from Google. Then, we integrate these three approaches into an integrated
one, which is named MIWA. Experimental results show that the integrated
approach MIWA has better performance: F-measure reaches 0.615, which is
higher than that of each independent one. |
| 42 |
Efficient Index Maintenance for Frequently Updated Semantic Data |
- Yan Liang*, Shanghai Jiao Tong University
- Haofen Wang, Shanghai Jiao Tong University
- Qiaoling Liu, Shanghai Jiao Tong University
- Thanh Tran, Institute AIFB, University Karlsruhe
- Thomas PENIN, Shanghai Jiao Tong University
- Yong Yu, Shanghai Jiao Tong University
|
Nowadays, the demand on querying and searching the Semantic Web is increasing.
Some systems have adopted IR (Information Retrieval) approaches to index
and search the Semantic Web data due to its capability to handle the web-scale
data and efficiency on query answering. Additionally, the huge volumes of
data on the Semantic Web are frequently updated. Thus, it further requires
effective update mechanisms for these systems to handle the data change.
However, the existing update approaches only focus on document. It still
remains a big challenge to update IR index specially designed for semantic
data in the form of finer grained structured objects rather than unstructured
documents. In this paper, we present a well-designed update mechanism on
the IR index for triples. Our approach provides flexible and effective update
mechanism by dividing the index into blocks. It reduces the number of update
operations during the insertion of triples. At the same time, it preserves
the efficiency on query processing and the capability to handle large scale
semantic data. Experimental results show that the index update time is a
fraction of that by complete reconstruction w.r.t the portion of the inserted
triples. Moreover, the query response time is not notably affected. Thus,
it is capable to make newly arrived semantic data immediately searchable
for users. |
| 47 |
Predicting Category Additions in a Topic Hierarchy |
- Dunja Mladenic*, J. Stefan Institute, SL
- Janez Brank,
- Marko Grobelnik,J. Stefan Institute, SL
|
This paper discusses the problem of predicting the structural changes
in an ontology. It addresses ontologies that contain instances in addition
to concepts. The focus is on an ontology where the instances are textual
documents, but the approach presented in this document is general enough
to also work with other kinds of instances, as long as a similarity measure
can be defined over them. We examine the changes in the Open Directory Project
ontology of Web pages over a period of several years and analyze the most
common types of structural changes that took place during that time. We
then present an approach for predicting one of the more common types of
structural changes, namely the addition of a new concept that becomes the
subconcept of an existing parent concept and adopts a few instances of this
existing parent concept. We describe how this task can be formulated as
a machine-learning problem and present an experimental evaluation of this
approach that shows promising results of the proposed approach. |
| 60 |
ROC: a method for proto-ontology construction by domain experts |
- Nicole Koenderink*, WUR -- A&F
- Mark Van Assem, Vrije Universiteit Amsterdam
- J. Lars Hulzebos, Wageningen UR -- A&F
- Jeen Broekstra, Wageningen UR -- A&F
- Jan Top, Wageningen UR -- A&F
|
Ontology construction is a labour-intensive and costly process. Even though
many formal and semi-formal vocabularies are available, creating an ontology
for a specific application is hindered in a number of ways. Firstly, the
process of elicitating concepts is a time consuming and strenuous process.
Secondly, it is difficult to keep focus. Thirdly, technical modelling constructs
are hard to understand for the uninitiated. We propose ROC as a method to
cope with these problems. ROC builds on well-known approaches for ontology
construction. However, we reuse existing sources to generate a repository
of proposed associations. ROC assists in efficiently putting forward all
relevant concepts and relations by providing a large set of potential candidate
associations. Secondly, rather than using intermediate representations of
formal constructs we confront the domain expert with `natural-language-like'
statements generated from RDF-based triples. Moreover, we strictly separate
the roles of problem owner, domain expert and knowledge engineer, each having
his own responsibilities and skills. The domain expert and problem owner
keep focus by monitoring a well-defined application purpose. We have implemented
an initial set of tools to support ROC. This paper describes the ROC method
and two application cases in which we evaluate the overall approach. |
| 62 |
Towards a component-based framework for developing Semantic Web Applications |
- Raúl García Castro, Ontology Engineering Group
- Asun Gomez-Perez, Universidad Politecnica de Madrid,
- Óscar Muñoz-García*, Ontology Engineering Group
- Lyndon Nixon, AG Netzbasierte Informationssysteme
|
For people outside of the research community, starting Semantic Web application
development is difficult. While Semantic Web tools reach industrial maturity,
there is still a lack of usable approaches for the planning of Semantic
Web solutions. We propose the Semantic Web Framework, a component-based
framework for the quick analysis of the required components, the dependencies
between them, and selection of existing solutions. This approach has been
tested with a number of industrial partners, justifying further e ffort
in this direction. |
| 67 |
A Pattern Based Approach for Re-engineering Non-Ontological Resources
into Ontologies |
- Boris Villazón-Terrazas*, OEG - DIA - FI - UPM
- Asun Gomez-Perez, Universidad Politecnica de Madrid,
- ES Mari Carmen Suarez-Figueroa, OEG - DIA - FI - UPM
- Andres Garcia-Silva, OEG - DIA - FI - UPM
|
With the goal of speeding up the ontology development process, ontology
engineers are starting to reuse as much as possible other ontologies as
well as knowledge-aware resources such as classification schemes, thesauri,
lexicons and folksonomies built by others that already have some degree
of consensus. The reuse of such resources involves necessarily their re-engineering
into ontologies. Non-ontological resources are highly heterogeneous; they
encode different types of knowledge, and also they can be modeled and implemented
in different ways. In this paper we present a typology for non-ontological
resources, a pattern based approach for re-engineering non-ontological resources
into ontologies, and a use case of the proposed approach. |
| 68 |
Deriving concept mappings through instance mappings |
- Shenghui Wang*, Vrije Universiteit Amsterdam
- Balthasar Schopman, Vrije Universiteit Amsterdam
- Stefan Schlobach, Vrije Universiteit Amsterdam, NL
|
Ontology matching is a promising step towards the solution to the interoperability
problem of the Semantic Web. Instance-based methods have the advantage of
focusing on the most active parts of the ontologies and reflect concept
semantics as they are actually being used. Previous instance-based mapping
techniques were only applicable to cases where a substantial set of instances
shared by both ontologies. In this paper, we propose to use a lexical search
engine to map instances from different ontologies. By exchanging concept
classification information between these mapped instances, an artificial
set of common instances is built, on which existing instance-based methods
can apply. Our experiment results demonstrate the effectiveness and applicability
of this method to a broad mapping context. |
| 72 |
Temporal Ontology Language for Representing and Reasoning Interval-based
Temporal Knowledge |
- Sang-Kyun Kim*, KIOM
- Kyu-Chul Lee,
- Mi-Young Song,
|
Recently, W3C Web Ontology working group has developed OWL as an ontology
language for the Semantic Web. However, because OWL does not have the full-fledged
semantics for temporal information, it cannot perform reasoning about temporal
knowledge. Entities in the real world are changing according to the passage
of time and new facts are occurring due to events. Thus, if knowledge in
the KBs does not have the temporal information, it becomes incomplete and
incorrect. Therefore, in this thesis we propose an ontology language TL-OWL,
which extends OWL to have the temporal semantics in order to represent and
reason the temporal information in the Semantic Web. |
| 75 |
A Formal Semantics-Preserving Translation from Fuzzy Relational Database
Schema to Fuzzy OWL DL Ontology |
- Fu Zhang*, Northeastern University
- Z.M Ma, , Northeastern University
- Hailong Wang, , Northeastern University
- Xiangfu Meng, , Northeastern University
|
How to construct Web ontologies has become a key technology to enable
the Semantic Web, especially how to construct ontologies by extracting domain
knowledge from database models such as the relational database model. But
in real-world applications, information is often imprecise and uncertain,
thus the formal approach to translation from Fuzzy Relational Database Schema
(FRDS) to fuzzy ontology is helpful for extracting domain knowledge from
database, which can profitably support fuzzy ontology development and developing
data-intensive Semantic Web applications. In this paper, we first give the
formal definition of FRDS. Then, the formal definition and Model-Theoretic
semantics of a kind of new fuzzy OWL DL ontology are given in more detail.
What’s more, we realize the formal translation from FRDS to fuzzy
OWL DL ontology by means of reverse engineering technique. Of course, the
correctness of translation is also proved. With an example, it shows that
the translation method is semantics-preserving and effective. Finally, the
reasoning problem of satisfiability, subsumption, and redundancy of FRDS
may reason automatically through reasoning mechanism of the corresponding
fuzzy description logic f-SHOIN(D) of fuzzy OWL DL ontology is also investigated,
which can further contribute to constructing fuzzy OWL DL ontologies exactly
that meet application’s needs well. |
| 76 |
STAN: Social, Trusted Annotation Network |
- Hyun Namgoong*, Seoul National University
- Kyoung-Mo Yang, SunMoon University
- Sung-Kwon Yang, Seoul National University
- Charles Borchert, Seoul National University
- Hong-Gee Kim, Seoul National University
|
Annotated data play an important role in enhancing the usability of information
resources. Single users can be easily frustrated by the task of annotating.
Collaborative approaches to annotation have been applied to web resources,
but have not yet been applied to the task of local documents, due in part
to the lack of a uniform identification method. In this paper, we use hash-based
virtual URIs for identifying documents, and introduce the concept of a STAN
(Social, Trusted Annotation Network), which enables collaborative annotation
of documents through their URIs. STAN also incorporates quantitative trust
rates between users in social networks based on their interactions with
each other. The STAN framework is described, demonstrating how these trust
networks are constructed through collaborative annotation. Finally, we evaluate
the usefulness of collaborative annotation and the feasibility of the resulting
trust rates through empirical experiment. |
| 77 |
Consolidating User-defined Concepts with StYLiD |
- Aman Shakya*, NII, Japan
- Hideaki Takeda, National Institute of Informatics, JP
- Vilas Wuwongse, Asian Institute of Technology
|
Information sharing can be effective with structured data. However, there
are several challenges for having structured data on the web. Creating structured
concept definitions is difficult and multiple conceptualizations may exist
due to different user requirements and preferences. We propose consolidating
multiple concept definitions into a unified virtual concept and formalize
our approach. We have implemented a system called StYLiD to realize this.
StYLiD is a social software for sharing a wide variety of structured data.
Users can freely define their own structured concepts. The system consolidates
multiple definitions for the same concept by different users. Attributes
of the multiple concept versions are aligned semi-automatically to provide
a unified view. It provides a flexible interface for easy concept definition
and data contribution. Popular concepts gradually emerge from the cloud
of concepts while concepts evolve incrementally. StYLiD supports linked
data by interlinking data instances including external resources like Wikipedia. |
| 78 |
Refining instance coreferencing results using belief propagation |
- Andriy Nikolov*, Open University
- Victoria Uren, KMi The Open University
- Enrico Motta, KMi, the Open University
- Anne De Roeck, Open University
|
The problem of coreference resolution (finding individuals, which describe
the same entity but have different URIs) is crucial when dealing with semantic
data coming from different sources. Specific features of Semantic Web data
(ontological constraints, data sparseness, varying quality of sources) are
all significant for coreference resolution and must be exploited. In this
paper we present a framework, which uses Dempster-Shafer belief propagation
to capture these features and refine coreference resolution results produced
by simpler string similarity techniques. |
| 80 |
Exposing heterogeneous data sources as SPARQL endpoints through an object-oriented
abstraction |
- Walter Corno, CEFRIEL
- Francesco Corcoglioniti, CEFRIEL
- Irene Celino*, Cefriel
- Emanuele Della Valle, CEFRIEL
|
The Web of Data vision raises the problem of how to expose existing data
sources on the Web without requiring heavy manual work. In this paper, we
present our approach to facilitate SPARQL queries over heterogeneous data
sources. We propose the use of an object-oriented abstraction which can
be automatically mapped and translated into an ontological one; this approach,
on the one hand, helps data managers to disclose their sources without the
need of a deep understanding of Semantic Web technologies and standards
and, on the other hand, takes advantage of object-relational mapping (ORM)
technologies and tools to deal with different types of data sources (relational
DBs, but also XML sources, object-oriented DBs, LDAP, etc.). We introduce
both the theoretical foundations of our solution, with the analysis of the
relation and mapping between SPARQL algebra and monoid comprehension calculus
(the formalism behind object queries), and the implementation we are using
to prove the feasibility and the benefits of our approach and to compare
it with alternative methods. |
| 87 |
A Segmentation-based Approach for Approximate Query over Distributed Ontologies |
- Yimin Wang*, Lilly Singapore
- Peter Haase, University of Karlsruhe
- Guilin Qi, University of Karlsruhe
|
With the popularity of semantic information systems distributed on the
Web, there is an arising challenge to provide efficient query answering
support for these systems. However, common approaches for distributed query
answering either exhibit performance disadvantages or loss of completeness
in an unbalanced way. In this paper, we introduce a novel approach for segment-based
conjunctive query answering over distributed ontologies. Our approach balances
the trade-off between performance and completeness by introducing segmentation-based
distributed ontology integration. We define the notions of segment and approximate
conjunctive query answering. Corresponding algorithms are designed, implemented
and evaluated. The evaluation results show that our approach is very promising
in processing ontologies in modern semantic information systems. |
| 89 |
Identifying key concepts in an ontology, through the integration of cognitive
principles with statistical and topological measures |
- Silvio Peroni, KMi, the Open University
- Enrico Motta, KMi, the Open University
- Mathieu D'Aquin*, KMi, the Open University
|
In this paper we address the issue of identifying the concepts in an ontology
which best summarize what the ontology is about. Our approach combines a
number of criteria, drawn from cognitive science, network topology and lexical
statistics. In the paper we show two versions of our algorithm, which have
been evaluated against the results produced by human experts. We report
that the second version of the algorithm performed well, exhibiting a good
correlation with the choices of the experts. While the generation of automatic
methods for ontology summarization is an interesting research issue in itself,
the work described here also provides a basis for novel approaches to a
variety of ontology engineering tasks, including ontology matching, automatic
classification, ontology modularization, and ontology evaluation. |
| 91 |
Deep Semantic Mapping between Functional Taxonomies for Interoperable
Semantic Search |
- Yoshinobu Kitamura*, Osaka University
- Sho Segawa, Osaka University
- Munehiko Sasajima, Osaka University
- Riichiro Mizoguchi, Osaka University, JP
|
This paper discusses ontology mapping between two taxonomies of functions
of artifacts and its use in semantic search for the engineering knowledge
management. The mapping is of two ways and has been manually established
with deep semantic analysis based on a reference ontology of function for
bridging the ontological gaps between the taxonomies. We report on the successful
results thanks to such deep analysis not at the lexical level but at the
ontological level. Using the mapping knowledge, we developed a semantic
search system which can provide engineers with interoperable access to technical
documents by searching for functional metadata based on either of functional
taxonomies. Such function-oriented engineering knowledge management is very
useful in engineering design, for example, by finding previous design cases
for the same required function, by finding related patents, or by getting
ideas how to solve a problem in a current design. The developed document
search system based on semantic annotation representing functionality can
solve the difficulty of the conventional document management systems based
on the lexical keyword search by searching for technical documents in terms
of generic types of function defined in the functional taxonomies as metadata
schemata independently of the lexical words in the documents. |
| 92 |
A Robust Ontology-Based Method for Translating Natural Language Queries
to Conceptual Graphs |
- TRU CAO*, Ho Chi Minh City Uni. Of Tech.
|
A natural language interface is always desirable for a search system.
While performance of machine translation for general texts with acceptable
computational costs seems to reach a limit, narrowing down the domain to
one of queries reduces the complexity and enables better translation correctness.
This paper proposes a query translation method that is robust to ill-formed
questions and exploits knowledge of an ontology for semantic search. It
uses conceptual graphs as the target language for the translation. As a
logical interlingua with smooth mapping to and from natural language, conceptual
graphs simplify translation rules and can be easily converted to other formal
query languages. Experiment results of the method on the TREC 2002 and TREC
2007 data sets are also presented and discussed. |
| 104 |
Bounded Ontological Consistency for Scalable Dynamic Knowledge Infrastructures |
- Maciej Zurawski*, CISA, School of informatics
- Alan Smaill, CISA, School of Informatics, University of Edinburgh
- Dave Robertson, CISA, School of Informatics, University of Edinburgh
|
Both semantic web applications and individuals are in need of knowledge
infrastructures that can be used in dynamic and distributed environments
where different autonomous entities create knowledge and build their own
view of a domain. Our framework represents this using evolving simple contextual
ontologies and mappings between them, at the same time as incremental logical
coherence is maintained. The definition of semantic autonomy includes these
aspects. Our earlier research has shown that a knowledge infrastructure
can have semantic autonomy that maintains global consistency, if the knowledge
representation is kept simple. We generalize that research by investigating
what happens if the consistency of a knowledge infrastructure is bounded
1) within certain regions called spheres of consistency, and 2) by allowing
a limited variable degree of inconsistency. Our experiments show that a
phase transition can occur in this kind of system, beyond which constant-time
and constant-memory complexity is approached. |
| 107 |
Understanding Semantic Web Applications |
- Kouji Kozaki*, Osaka University Yusuke
- Hayashi, I.S.I.R.,Osaka University Munehiko
- Sasajima, Osaka University Riichiro
- Mizoguchi, Osaka University, JP
|
Ten years have passed since the concept of the semantic web was proposed
by Tim Berners-Lee. For these years, basic technologies for them such as
RDF(S) and OWL were published. As a result, many systems using semantic
technologies have been developed. Some of them are not prototype systems
for researches but real systems for practical use. The authors analyzed
semantic web applications published in the semantic web conferences (ISWC,
ESWC, ASWC) and classified them based on ontological engineering. This article
discusses a trend and the future view of them using the results. |
| 109 |
A Formal Model for Classifying Trusted Semantic Web Services |
- Stefania Galizia*, Open University, UK
- Alessio Gugliotta, Open University, UK
|
Semantic Web Services (SWS) aim to alleviate Web service limitations,
by combining Web service technologies with the potentiality of Semantic
Web. Several open issues have to be tackled yet, in order to enable a safe
and efficient Web services selection. One of them is represented by trust.
In this paper, we introduce a trust definition and formalize a model for
managing trust in SWS. The model embeds the trusted Web service selection
in a classification problem, and it is realized by an ontology, which extends
WSMO. A prototype is deployed, in order to give a proof of concept of our
approach. |
| 113 |
An editorial work๏ฌ‚ow approach for collaborative ontology
development |
- Raul Palma*, UPM
- Peter Haase, University of Karlsruhe
- Oscar Corcho, UPM
- Asun Gomez-Perez, Universidad Politecnica de Madrid, ES
|
The widespread use of ontologies in the last years has raised new challenges
for their development and maintenance. Ontology development has transformed
from a process normally performed by one ontology engineer into a process
performed collaboratively by a team of ontology engineers, who may be geographically
distributed and play different roles. For example, editors may propose changes,
while authoritative users approve or reject them following a well de?ned
process. This process, however, has only been partially addressed by existing
ontology development methods, methodologies, and tool support. Furthermore,
in a distributed environment where ontology editors may be working on local
copies of the same ontology, strategies should be in place to ensure that
changes in one copy are re?ected in all of them. In this paper, we propose
a work?ow-based model for the collaborative development of ontologies in
distributed environments and describe the components required to support
them. We illustrate our model with a test case in the ?shery domain from
the United Nations Food and Agriculture Organisation (FAO). |
| 114 |
Versatile Semantic Modeling of Frame Logic Programs under Answer Set Semantics |
- Mario Alviano, Universita Della Calabria
- Giovambattista Ianni*, University of Calabria
- Marco Marano, Universita Della Calabria
- Alessandra Martello, Universita Della Calabria
|
This work introduces the framework of Frame Answer Set programs (FAS).
FAS programs are a frame logic-like language working under answer set semantics
augmented with higher order constructs. The syntax of the language includes
the possibility to manipulate nested molecules, class hierarchies, basic
method signatures and contexts (called framespaces). Semantics is defined
in terms of a corresponding stable model semantics, paving the way to model
object ontologies and their semantics under this well known paradigm. The
language is purposely designed so that inheritance behavior and other features
of the language can be easily customized by the introduction of specialized
axiomatic modules, which can be modeled on purpose by advanced developers
of ontology languages. Also, contexts allow to model hybrid systems integrating
multiple data sources working under different entailment regimes. Properties
and relationship with original F-logic semantics of some of the presented
axiomatizations are given. A system prototype has been implemented and is
available for evaluation. |
| 115 |
Semantic Assistants -- User-Centric Natural Language Processing Services
for Desktop Clients |
- René Witte*, Concordia University
- Thomas Gitzinger, University of Karlsruhe
|
Today's knowledge workers have to spend a large amount of time and manual
effort on creating, analyzing, and modifying textual content. While more
advanced semantically-oriented analysis techniques have been developed in
recent years, they have not yet found their way into commonly used desktop
clients, be they generic (e.g., word processors, email clients) or domain-specific
(e.g., software IDEs, biological tools). Instead of forcing the user to
leave his current context and use an external application, we propose a
``Semantic Assistants'' approach, where semantic analysis services relevant
for the user's current task are offered directly within a desktop application.
Our approach relies on an OWL ontology model for context and service information
and integrates external natural language processing (NLP) pipelines through
W3C Web services. |
| 120 |
Named Entity Disambiguation: A Hybrid Statistical and Rule-based Incremental
Approach |
- Hien Nguyen*, Ton Duc Thang University
- TRU CAO, Ho Chi Minh City Uni. Of Tech.
|
The rapidly increasing use of large-scale data on the Web makes named
entity disambiguation become one of the main challenges to research in Information
Extraction and development of Semantic Web. This paper presents a novel
method for detecting proper names in a text and linking them to the right
entities in Wikipedia. The method is hybrid, containing two phases of which
the first one utilizes some heuristics and patterns to narrow down the candidates,
and the second one employs the vector space model to rank the ambiguous
cases to choose the right candidate. The novelty is that the disambiguation
process is incremental and includes several rounds that filter the candidates,
by exploiting previously identified entities and extending the text by those
entity attributes every time they are successfully resolved in a round.
We test the performance of the proposed method in disambiguation of names
of people, locations and organizations in texts of the news domain. The
experiment results show that our approach achieves high accuracy and can
be used to construct a robust named entity disambiguation system. |
| 122 |
Exploiting Gene Ontology to Conceptualize Biomedical Document Collections |
- Hai-Tao Zheng*, Seoul National University
- Charles Borchert, Seoul National University
- Hong-Gee Kim, Seoul National University
|
As biomedical science progresses, ontologies play an increasingly important
role in easing the understanding of biomedical information. Although much
research, such as Gene Ontology annotation, has been proposed to utilize
ontologies to help users understand biomedical information easily, most
of the research does not focus on capturing gene-related terms and their
relationships within biomedical document collections. Understanding key
gene-related terms as well as their semantic relationships is essential
for comprehending the conceptual structure of biomedical document collections
and avoiding information overload for users. To address this issue, we propose
a novel approach called `GOClonto' to automatically generate ontologies
for conceptualization of biomedical document collections. Based on GO (Gene
Ontology), GOClonto extracts gene-related terms from biomedical text, applies
latent semantic analysis to identify key gene-related terms, allocates documents
based on the key gene-related terms, and utilizes GO to automatically generate
a corpus-related gene ontology. The experimental results show that GOClonto
is able to identify key gene-related terms. For a test biomedical document
collection, GOClonto shows better performance than the other clustering
algorithms in terms of F-measure. Moreover, the ontology generated by GOClonto
shows a significant informative conceptual structure. |
| 123 |
SAOR: Authoritative Reasoning for the Web |
- Aidan Hogan*, DERI Galway
- Axel Polleres, DERI Galway
- Andreas Harth, DERI Galway
|
In this paper we discuss the challenges of performing reasoning on large
scale RDF datasets from the Web. We discuss issues and practical solutions
relating to reasoning over web data using a rule-based approach to forward-chaining;
in particular, we identify the problem of ontology hijacking: new ontologies
published on the Web re-defining the semantics of existing concepts resident
in other ontologies. Our solution introduces consideration of authoritative
sources. Our system is designed to scale, comprising file-scans and selected
lightweight on-disk indices. We evaluate our methods on a dataset in the
order of a hundred million statements collected from real-world Web sources. |
| 125 |
Scalable Distributed Ontology Reasoning Using DHT-based Partitioning |
- Qiming Fang*, Tsinghua University
- Ying Zhao,
- Guangwen Yang,
- Weimin Zheng,
|
Ontology reasoning is an indispensable step to fully exploit the implicit
semantics of Semantic Web data. The inherent distribution characteristic
of Semantic Web and huge amount of ontology instance data necessitates efficient
and scalable distributed ontology reasoning. Current researches on distributed
ontology reasoning mainly focus on dealing with the heterogeneity of different
ontologies but pay little attention to the performance of distributed reasoning
and have not presented practical approaches and systems. Our goal is to
propose an efficient and scalable distributed ontology reasoning approach,
making it practical in real semantic applications. We propose an approach
in this paper, in which Description Logic reasoners for TBox reasoning are
com-bined with rule engines for ABox reasoning to support both expressive
ontolo-gies and large amount of instance data. The published data from each
node is distributed using a DHT-based partitioning and stored in well-designed
rela-tional databases to support convenient and efficient reasoning through
coopera-tion of the distributed nodes. A practical distributed ontology
reasoning and querying system called DORS is developed based on our proposed
approach. Our experiments both in LANs and on PlanetLab using University
Ontology Benchmark show high efficiency of DORS compared with the centralized
OWL ontology reasoning system Minerva as well as good scalability with respect
to the number of nodes and volume of data in the system. |
| 126 |
Extracting Semantic Frames from Thai Medical-Symptom Phrases with Unknown
Boundaries |
- Peerasak Intarapaiboon,
- Ekawit Nantajeewarawat*, Sirindhorn International Institute of Technology,
Thailand
- Thanaruk Theeramunkong,
|
Due to the limitations of language-processing tools for the Thai language,
pattern-based information extraction from Thai documents requires supplementary
techniques. Based on sliding-window rule application and extraction filtering
components, we present a framework for extracting semantic information from
medical-symptom phrases with unknown boundaries in Thai free-text information
entries. A supervised rule learning algorithm is employed for automatic
creation of information extraction rules from manually prepared training
data. Classification models are constructed for prediction of rule application
across a symptom-phrase boundary. Overlapping extracted frames are removed
based on extraction distances observed during rule learning. In our experimental
study, we focus our attention on two basic types of symptom phrasal descriptions:
one is concerned with abnormal characteristics of some observable entities
and the other with human-body locations at which symptoms appear. The experimental
results show that the filtering components improve precision satisfactorily
while preserving high recall, overcoming the classical trade-off between
them. |
| 127 |
A Tableau Algorithm for Possibilistic Description Logic ALC |
- Guilin Qi*, University of Karlsruhe
- Jeff Pan, University of Aberdeen, UK
|
Uncertainty reasoning and inconsistency handling are two important problems
that often occur in the applications of the Semantic Web. Possibilistic
description logics provide a flexible framework for representing and reasoning
with ontologies where uncertain and/or inconsistent information is available.
Although possibilistic logic has become a popular logical framework for
uncertainty reasoning and inconsistency handling, its role in the Semantic
Web is underestimated. One of the challenging problems is to provide a practical
algorithm for reasoning in possibilistic description logics. In this paper,
we propose a tableau algorithm for possibilistic description logic ALC.
We show how inference services in possibilistic ALC can be reduced to the
problem of computing the inconsistency degree of the knowledge base. We
then give tableau expansion rules for computing the inconsistency degree
of a possibilistic ALC knowledge. We show that our algorithm is sound and
complete. The computational complexity of our algorithm is analyzed. Since
our tableau algorithm is an extension of a tableau algorithm for ALC, we
can reuse many optimization techniques for tableau algorithms of ALC to
improve the performance of our algorithm so that it can be applied in practice. |