BibSonomyburst/user/conchuirBibSonomy RSS feed for /user/conchuir2012-02-15T13:56:44+01:00http://www.bibsonomy.org/bibtex/2df4522f759d390b073d3474eb9a05b27/conchuirconchuir2009-02-13T13:22:04+01:00aswc08 <span class="authorEditorList"><a href="/author/Galizia">Stefania Galizia</a>, <a href="/author/Gugliotta">Alessio Gugliotta</a>, and <a href="/author/Pedrinaci">Carlos Pedrinaci</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web540--554A Formal Model for Classifying Trusted Semantic Web Services2008aswc08 Semantic Web Services (SWS) aim to alleviate Web service limitations, by combining Web service technologies with the potential 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 approaches the selection of trusted Web services as 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.http://www.bibsonomy.org/bibtex/22548c426f71e1735d58ecd9367a8db02/conchuirconchuir2009-02-13T13:22:04+01:00aswc08 <span class="authorEditorList"><a href="/author/Zhang">Fu Zhang</a>, <a href="/author/Ma">Z. Ma</a>, <a href="/author/Wang">Hailong Wang</a>, and <a href="/author/Meng">Xiangfu Meng</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web46--60A Formal Semantics-Preserving Translation from Fuzzy Relational Database Schema to Fuzzy OWL DL Ontology2008aswc08 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 (FRDBS) 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 FRDBS. 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 FRDBS 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 FRDBS 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.http://www.bibsonomy.org/bibtex/23901dc7459732be9e86e287361f5d93b/conchuirconchuir2009-02-13T13:22:04+01:00OWL aswc08 <span class="authorEditorList"><a href="/author/Suntisrivaraporn">Boontawee Suntisrivaraporn</a>, <a href="/author/Qi">Guilin Qi</a>, <a href="/author/Ji">Qiu Ji</a>, and <a href="/author/Haase">Peter Haase</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web1--15A Modularization-Based Approach to Finding All Justifications for OWL DL Entailments2008OWL aswc08 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 efficiency and scalability of finding all justifications in OWL DL ontologies.http://www.bibsonomy.org/bibtex/298096132b1eb4b4b5b0de3cec6a22de5/conchuirconchuir2009-02-13T13:22:04+01:00aswc08 <span class="authorEditorList"><a href="/author/Garc\&#039;ia-Silva">Andrés Garc\&#039;ia-Silva</a>, <a href="/author/Gómez-Pérez">Asunción Gómez-Pérez</a>, <a href="/author/Suárez-Figueroa">Mari Suárez-Figueroa</a>, and <a href="/author/Villazón-Terrazas">Boris Villazón-Terrazas</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web167--181A Pattern Based Approach for Re-engineering Non-Ontological Resources into Ontologies2008aswc08 With the goal of speeding up the ontology development process, ontology engineers are starting to reuse as much as possible available ontologies and non-ontological resources such as classification schemes, thesauri, lexicons and folksonomies, that already have some degree of consensus. The reuse of such non-ontological resources necessarily involves their re-engineering into ontologies. Non-ontological resources are highly heterogeneous in their data model and contents: they encode different types of knowledge, and they can be modeled and implemented in different ways. In this paper we present (1) a typology for non-ontological resources, (2) a pattern based approach for re-engineering non-ontological resources into ontologies, and (3) a use case of the proposed approach.http://www.bibsonomy.org/bibtex/26d6b651e543ee96997d5d67f71df9560/conchuirconchuir2009-02-13T13:22:04+01:00aswc08 <span class="authorEditorList"><a href="/author/Cao">Tru Cao</a>, <a href="/author/Cao">Truong Cao</a>, and <a href="/author/Tran">Thang Tran</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web479--492A Robust Ontology-Based Method for Translating Natural Language Queries to Conceptual Graphs2008aswc08 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.http://www.bibsonomy.org/bibtex/2c04897e1d45228c465c5c1c4b6dd9d8e/conchuirconchuir2009-02-13T13:22:04+01:00aswc08 <span class="authorEditorList"><a href="/author/Wang">Yimin Wang</a>, <a href="/author/Qi">Guilin Qi</a>, and <a href="/author/Chen">Min Chen</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web464--478A Segmentation-Based Approach for Approximate Query over Distributed Ontologies2008aswc08 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.http://www.bibsonomy.org/bibtex/27a13026b1a878657524484213e97f42d/conchuirconchuir2009-02-13T13:22:04+01:00aswc08 <span class="authorEditorList"><a href="/author/Qi">Guilin Qi</a>, and <a href="/author/Pan">Jeff Pan</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web61--75A Tableau Algorithm for Possibilistic Description Logic2008aswc08 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 . We show how inference services in possibilistic 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 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 , we can reuse many optimization techniques for tableau algorithms of to improve the performance of our algorithm so that it can be applied in practice.http://www.bibsonomy.org/bibtex/2b113b03563b06a91d762b69f4cb61ce5/conchuirconchuir2009-02-13T13:22:04+01:00aswc08 <span class="authorEditorList"><a href="/author/Palma">Raúl Palma</a>, <a href="/author/Haase">Peter Haase</a>, <a href="/author/Corcho">Oscar Corcho</a>, <a href="/author/Gómez-Pérez">Asunción Gómez-Pérez</a>, and <a href="/author/Ji">Qiu Ji</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web227--241An Editorial Workflow Approach For Collaborative Ontology Development2008aswc08 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 defined 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 reflected in all of them. In this paper, we propose a workflow-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 fishery domain from the United Nations Food and Agriculture Organisation (FAO).http://www.bibsonomy.org/bibtex/24f9b9f151c46f0c40b5e391877c4631b/conchuirconchuir2009-02-13T13:22:04+01:00aswc08 <span class="authorEditorList"><a href="/author/Xu">Renjie Xu</a>, <a href="/author/Gao">Zhiqiang Gao</a>, <a href="/author/Pan">Yingji Pan</a>, <a href="/author/Qu">Yuzhong Qu</a>, and <a href="/author/Huang">Zhisheng Huang</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web302--314An Integrated Approach for Automatic Construction of Bilingual Chinese-English WordNet2008aswc08 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.http://www.bibsonomy.org/bibtex/2513e22aa3f1f96be110ce6f020572593/conchuirconchuir2009-02-13T13:22:04+01:00aswc08 <span class="authorEditorList"><a href="/author/Zurawski">Maciej Zurawski</a>, <a href="/author/Smaill">Alan Smaill</a>, and <a href="/author/Robertson">Dave Robertson</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web212--226Bounded Ontological Consistency for Scalable Dynamic Knowledge Infrastructures2008aswc08 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.http://www.bibsonomy.org/bibtex/2b40b75c66d769c59c52f295ba1e22015/conchuirconchuir2009-02-13T13:22:04+01:00aswc08 <span class="authorEditorList"><a href="/author/Liu">Qiaoling Liu</a>, <a href="/author/Xu">Kaifeng Xu</a>, <a href="/author/Zhang">Lei Zhang</a>, <a href="/author/Wang">Haofen Wang</a>, <a href="/author/Yu">Yong Yu</a>, and <a href="/author/Pan">Yue Pan</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web330--344Catriple: Extracting Triples from Wikipedia Categories2008aswc08 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 properties, which is too effort-consuming and explores only very limited knowledge in the categories. This paper automatically extracts properties and 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.http://www.bibsonomy.org/bibtex/24a1acffc6d4a99754ea12464358993f4/conchuirconchuir2009-02-13T13:22:04+01:00aswc08 <span class="authorEditorList"><a href="/author/Shakya">Aman Shakya</a>, <a href="/author/Takeda">Hideaki Takeda</a>, and <a href="/author/Wuwongse">Vilas Wuwongse</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web287--301Consolidating User-Defined Concepts with StYLiD2008aswc08 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.http://www.bibsonomy.org/bibtex/26e332eaafa87a7c44f1a6ebc6983adeb/conchuirconchuir2009-02-13T13:22:04+01:00aswc08 <span class="authorEditorList"><a href="/author/Kitamura">Yoshinobu Kitamura</a>, <a href="/author/Segawa">Sho Segawa</a>, <a href="/author/Sasajima">Munehiko Sasajima</a>, <a href="/author/Tarumi">Shinya Tarumi</a>, and <a href="/author/Mizoguchi">Riichiro Mizoguchi</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web137--151Deep Semantic Mapping between Functional Taxonomies for Interoperable Semantic Search2008aswc08 This paper discusses ontology mapping between two taxonomies of functions of artifacts 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.http://www.bibsonomy.org/bibtex/2db601664fa88adcb0e6db9bcbd51c281/conchuirconchuir2009-02-13T13:22:04+01:00aswc08 <span class="authorEditorList"><a href="/author/Schopman">Balthasar Schopman</a>, <a href="/author/Wang">Shenghui Wang</a>, and <a href="/author/Schlobach">Stefan Schlobach</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web122--136Deriving Concept Mappings through Instance Mappings2008aswc08 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 in broad thesaurus mapping context.http://www.bibsonomy.org/bibtex/2e2a96309a92f1a1ca6e389ad8e878a4d/conchuirconchuir2009-02-13T13:22:04+01:00aswc08 <span class="authorEditorList"><a href="/author/Kontchakov">Roman Kontchakov</a>, and <a href="/author/Zakharyaschev">Michael Zakharyaschev</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web16--30DL  −  Lite and Role Inclusions2008aswc08 We give a classification of the complexity of DL-Lite logics extended with role inclusion axioms. We show that 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 primitive concept inclusions. The combined complexity of satisfiability in this case jumps to ExpTime. On the other side, 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.http://www.bibsonomy.org/bibtex/28573f5446157c0ec23ab03b5b3cf41c1/conchuirconchuir2009-02-13T13:22:04+01:00aswc08 <span class="authorEditorList"><a href="/author/Liang">Yan Liang</a>, <a href="/author/Wang">Haofen Wang</a>, <a href="/author/Liu">Qiaoling Liu</a>, <a href="/author/Tran">Thanh Tran</a>, <a href="/author/Penin">Thomas Penin</a>, and <a href="/author/Yu">Yong Yu</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web182--196Efficient Index Maintenance for Frequently Updated Semantic Data2008aswc08 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 a 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.http://www.bibsonomy.org/bibtex/29b452dbb0180102a6c50f8b67db98cf8/conchuirconchuir2009-02-13T13:22:04+01:00aswc08 <span class="authorEditorList"><a href="/author/Zheng">Hai-Tao Zheng</a>, <a href="/author/Borchert">Charles Borchert</a>, and <a href="/author/Kim">Hong-Gee Kim</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web375--389Exploiting Gene Ontology to Conceptualize Biomedical Document Collections2008aswc08 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 other clustering algorithms in terms of F-measure. Moreover, the ontology generated by GOClonto shows a significant informative conceptual structure.http://www.bibsonomy.org/bibtex/209946d09e19f2eab9318644f9412e234/conchuirconchuir2009-02-13T13:22:04+01:00aswc08 <span class="authorEditorList"><a href="/author/Corno">Walter Corno</a>, <a href="/author/Corcoglioniti">Francesco Corcoglioniti</a>, <a href="/author/Celino">Irene Celino</a>, and <a href="/author/Valle">Emanuele Della Valle</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web434--448Exposing Heterogeneous Data Sources as SPARQL Endpoints through an Object-Oriented Abstraction2008aswc08 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.http://www.bibsonomy.org/bibtex/2952eb7df17071606d2c26bf3ec30fcb9/conchuirconchuir2009-02-13T13:22:04+01:00aswc08 <span class="authorEditorList"><a href="/author/Intarapaiboon">Peerasak Intarapaiboon</a>, <a href="/author/Nantajeewarawat">Ekawit Nantajeewarawat</a>, and <a href="/author/Theeramunkong">Thanaruk Theeramunkong</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web390--404Extracting Semantic Frames from Thai Medical-Symptom Phrases with Unknown Boundaries2008aswc08 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, 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 construction of information extraction rules from hand-tagged training symptom phrases. Two filtering components are introduced: one uses a classification model for predicting rule application across a symptom-phrase boundary, the other uses extraction distances observed during rule learning for resolving conflicts arising from overlapping-frame extractions. 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 while preserving recall satisfactorily.http://www.bibsonomy.org/bibtex/2201ac21acba87ae08a2339bb0469cc0b/conchuirconchuir2009-02-13T13:22:04+01:00aswc08 <span class="authorEditorList"><a href="/author/Peroni">Silvio Peroni</a>, <a href="/author/Motta">Enrico Motta</a>, and <a href="/author/D’aquin">Mathieu D’aquin</a> </span>(<em>2008</em>)Fri Feb 13 13:22:04 CET 2009The Semantic Web242--256Identifying Key Concepts in an Ontology, through the Integration of Cognitive Principles with Statistical and Topological Measures2008aswc08 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 latest version of the algorithm performs very well, exhibiting an excellent degree of 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.