Description logics for fuzzy ontologies on semantic web

To enable representation and reasoning for fuzzy ontologies with expressive fuzzy knowledge on the semantic web, a new fuzzy extension of description logics called the fuzzy description logics with comparison expressions （FCDLs） is presented. The syntax and semantics of FCDLs are formally defined, and the forms of axioms and assertions in FCDLs knowledge bases are specified. FCDLs combine both fuzzy concepts from the fuzzy description logics （FDLs） and cut concepts from the extended fuzzy description logics （EFDLs） in the same theory. Furthermore, cut concepts are extended into comparison cut concepts in FCDLs to represent comparison expressions between fuzzy membership degrees, which are often used in practice but not supported by the other fuzzy extensions of description logics. FCDLs have more expressive power than FDLs and EFDLs, and are able to represent expressive fuzzy knowledge and to perform reasoning tasks based on them. Therefore, FCDLs can enable representation and reasoning for fuzzy ontologies with expressive fuzzy knowledge on the semantic web.

Novel method for searching ontologies on semantic web

In order to solve the problem of information retrieval on the semantic web, a new semantic information retrieval （SIR） model for searching ontologies on the semantic web is proposed. First, SIR transformed domain ontologies into global ontologies. Then semantic index terms were extracted from these global ontologies. Based on semantic index terms, logical inferences can be performed and the logical views of the concept can be obtained. These logical views represent the expanded meaning of the concept. Using logical views, SIR can perform the information retrieval and inferences based on the semantic relationships in the documents, not only on the syntactic analysis of the documents. SIR can significantly enhance the recall and precision of the information retrieval by the semantic inference. Finally, the practicability of the SIR model is analyzed.

Kullback-Leibler distance based concepts mapping between web ontologies

A Kullback-Leibler（KL）distance based algorithm is presented to find the matches between concepts from different ontologies. First, each concept is represented as a specific probability distribution which is estimated from its own instances. Then, the similarity of two concepts from different ontologies is measured by the KL distance between the corresponding distributions. Finally, the concept-mapping relationship between different ontologies is obtained. Compared with other traditional instance-based algorithms, the computing complexity of the proposed algorithm is largely reduced. Moreover, because it proposes different estimation and smoothing methods of the concept distribution for different data types, it is suitable for various concepts mapping with different data types. The experimental results on real-world ontology mapping illustrate the effectiveness of the proposed algorithm.

Facilitating transparency in spinal cord injury studies using data standards and ontologies

Progress in developing robust therapies for spinal cord injury （SCI）, trau- matic brain injury （TBI） and peripheral nerve injury has been slow. A great deal has been learned over the past 30 years regarding both the intrinsic factors and the environmental factors that regulate axon growth, but this large body of information has not yet resulted in clinically available thera- peutics. This therapeutic bottleneck has many root causes, but a consensus is emerging that one contributing factor is a lack of standards for experi- mental design and reporting. The absence of reporting standards, and even of commonly accepted definitions of key words, also make data mining and bioinformatics analysis of neural plasticity and regeneration difficult, if not impossible. This short review will consider relevant background and poten- tial solutions to this problem in the axon regeneration domain.

Commentary on:“Facilitating transparency in spinal cord injury studies using data standards and ontologies”

Commentary Most would agree that providing comprehensive detail in scientific reporting is critical for the development of mean- ingful therapies and treatments for diseases. Such stellar practices 1） allow for reproduction of experiments to con- firm results, 2） promote thorough analyses of data, and 3） foster the incremental advancement of valid approaches. Unfortunately, most would also agree we have far to go to reach this vital goal （Hackam and Redelmeier, 2006; Prinz et al., 2011; Baker et al., 2014）.

Bridge Ontology: A Multi-Ontologies-Based Approach for Semantic Annotation

Representing the relationships between ontologies is the key problem of semantic annotations based on multi-ontologies. Traditional approaches only had the ability of denoting the simple concept subsumption relations between ontologies. Through analyzing and classifying the relationships between ontologies, the idea of bridge ontology was proposed, which had the powerful capability of expressing the complex relationships between concepts and relationships between relations in multi-ontologies. Meanwhile, a new approach employing bridge ontology was proposed to deal with the multi-ontologies-based semantic annotation problem. The bridge ontology is a peculiar ontology, which can be created and maintained conveniently, and is effective in the multi-ontologies-based semantic annotation. The approach using bridge ontology has the advantages of low-cost, scalable, robust in the web circumstance, and avoiding the unnecessary ontology extending and integration. Key words semantic web - bridge ontology - multi-ontologies - semantic annotation CLC number TP 391 Foundation item: Supported by the National Natural Science Foundation of China (60373066, 60303024). National Grand Fundamental Research 973 Program of China (2002CB312000), National Re-search Foundation for the Doctoral Program of Higher Education of China (20020286004)Biography: WANG Peng (1977-), male, Ph.D candidate, research direction: semantic web, ontology, and knowledge representation on the Web.

Extend OWL: toward a clustering integration of collaborative ontologies and agents

In order to solve the problem of how to collaborate with foreign agents and ontologies, a restricted clustering integration approach is proposed. It differs from the traditional approaches in which web ontology language （OWL） is extended by adding some new collaborative interfaces （ i. e., agent-link and ontology-link） to it instead of owl： import. Syntaxes of the interface for foreign ontologies and foreign agents, respectively, and a meta-method of clustering integrated collaboration are discussed. The approach focuses on taking advantage of OWL itself to solve the collaborative problems, and it is feasible to track the contexts of newadded knowledge concerning ontological collaboration.

Approximate querying between heterogeneous ontologies based on association matrix

An approximate approach of querying between heterogeneous ontology-basedinformation systems based on an association matrix is proposed. First, the association matrix isdefined to describe relations between concepts in two ontologies. Then, a methodof rewriting queriesbased on the association matrix is presented to solve the ontology heterogeneity problem. Itrewrites the queries in one ontology to approximate queries in another ontology based on thesubsumption relations between concepts. The method also uses vectors to represent queries, and thencomputes the vectors with the association matrix; the disjoint relations between concepts can beconsidered by the results. It can get better approximations than the methods currently in use, whichdonot consider disjoint relations. The method can be processed by machines automatically. It issimple to implement and expected to run quite fast.

Method of creating ontologies for Prolog clauses

A method is proposed to build an ontology in the form of a conceptual graph for Prolog clauses, so that the Prolog reasoning engine can differentiate clauses semantically to some degree. The concept model of a clauses ontology is composed of predicate parameters and head sub-goals, and these sub-goals appear in the head of the rule body and precede any predicate calls. In the proposed method, a Prolog program can be transformed into a Prolog ＋ CG program that includes a clauses ontology. Some experiments show that, with a clauses ontology, some clauses which do not match current goals are not considered early enough, and, therefore, the size of the goal solution tree may be reduced. By the capability of conceptual graph, a clauses ontology makes the semantics of the Prolog program more clear and readable, and sometimes it speeds up the solution process obviously.

Graphical Transformation of OWL Ontologies to Event-B Formal Models

Formal methods use mathematical models to develop systems.Ontologies are formal specifications that provide reusable domain knowledge representations.Ontologies have been successfully used in several data-driven applications,including data analysis.However,the creation of formal models from informal requirements demands skill and effort.Ambiguity,inconsistency,imprecision,and incompleteness are major problems in informal requirements.To solve these problems,it is necessary to have methods and approaches for supporting the mapping of requirements to formal specifications.The purpose of this paper is to present an approach that addresses this challenge by using theWeb Ontology Language(OWL)to construct Event-B formal models and support data analysis.Our approach reduces the burden of working with the formal notations of OWL ontologies and Event-B models and aims to analyze domain knowledge and construct Event-B models from OWL ontologies using visual diagrams.The idea is based on the transformation of OntoGraf diagrams of OWL ontologies to UML-B diagrams for the purpose of bridging the gap between OWL ontologies and Event-B models.Visual data exploration assists with both data analysis and the development of Event-B formal models.To manage complexity,Event-B supports stepwise refinement to allow each requirement to be introduced at themost appropriate stage in the development process.UML-B supports refinement,so we also introduce an approach that allows us to divide and layer OntoGraf diagrams.

Constructing Product Ontologies with an Improved Conceptual Clustering Algorithm

In a distributed eMarketplace, recommended product ontologies are required for trading between buyers and sellers. Conceptual clustering can be employed to build dynamic recommended product ontologies. Traditional methods of conceptual clustering (e.g. COBWEB or Cluster/2) do not take heterogeneous attributes of a concept into account. Moreover, the result of these methods is clusters other than recommended concepts. A center recommendation clustering algorithm is provided. According to the values of heterogeneous attributes, recommended product names can be selected at the clusters, which are produced by this algorithm. This algorithm can also create the hierarchical relations between product names. The definitions of product names given by all participants are collected in a distributed eMarketplace. Recommended product ontologies are built. These ontologies include relations and definitions of product names, which come from different participants in the distributed eMarketplace. Finally a case is given to illustrate this method. The result shows that this method is feasible.

Contextual Text Mining Framework for Unstructured Textual Judicial Corpora through Ontologies

Digitalization has changed the way of information processing, and newtechniques of legal data processing are evolving. Text mining helps to analyze andsearch different court cases available in the form of digital text documents toextract case reasoning and related data. This sort of case processing helps professionals and researchers to refer the previous case with more accuracy in reducedtime. The rapid development of judicial ontologies seems to deliver interestingproblem solving to legal knowledge formalization. Mining context informationthrough ontologies from corpora is a challenging and interesting field. Thisresearch paper presents a three tier contextual text mining framework throughontologies for judicial corpora. This framework comprises on the judicial corpus,text mining processing resources and ontologies for mining contextual text fromcorpora to make text and data mining more reliable and fast. A top-down ontologyconstruction approach has been adopted in this paper. The judicial corpus hasbeen selected with a sufficient dataset to process and evaluate the results.The experimental results and evaluations show significant improvements incomparison with the available techniques.

An Algebra of Ontologies Approximation under Uncertainty

Ontologies are widely used in modeling the real world for the purpose of information sharing and reasoning. Traditional ontologies contain only concepts and relations that describe asserted facts about the world. Modeling in a dynamic world requires taking into consideration the uncertainty that may arise in the domain. In this paper, the concept of soft sets initiated by Molodtsov and the concept of rough sets introduced by Pawlack are used to define a way of instantiating ontologies of vague domains. We define ontological algebraic operations and their properties while taking into consideration the uncertain nature of domains. We show that, by doing so, intra ontological operations and their properties are preserved and formalized as operations in a vague set of objects and can be proved algebraically.

User Interface Development Based on Ontologies

The user interface is a central component of any mo de rn application program. It determines how well end users accept, learn, and effi ciently work with the application program. The user interface is very difficult to design, to implement, to modify. It takes approximately 70% of the time requ ired for designing an application program. All the existing tools for user interface design can be divided into two basic c ategories-Interface Builders and Model-based Interface development tools, whic h trace their roots from user interface management systems. Interface Builders a re the most widespread and excellent to create layouts and manipulate widgets. H owever, Interface Builders have the follow demerits. An interface designed using Interface Builders can contain hundreds of procedures. Interface Builders give us no possibility to develop different pieces of the same interface separately. They do not help us in managing user tasks and can be used only by programmers. Model-based interface development tools have attracted a high degree of interes t in last few years. The basic premise of model based technology is that the interface development can be fully supported by declarative models of all user interface characteristics such as their presen tation, dialogue, domain of application etc, and then the user interface develop ment can be centered around such models. The high potential of this technology has not been realized yet. This fact has the following reasons. The known interface models are partial representations of interfaces. They cannot be readily modified by developers, and are not publicly available to the HCI community. The central ingredient for success in model-ba sed systems is a declarative, complete, versatile interface model that can expre ss a wide variety of interface designs. Therefore tool developers have to avoid the following disadvantages of current interface models: inflexibility, system- dependence, and incompleteness. The main idea to achieve these model character istics mention above is to use ontologies. This broadened interest in ontologies is based on the fact that they provide ma chine-understandable representation of semantics for information, and a shared and common understanding of a domain that can be communicated between people and across application systems. Support in data, information, and knowledge exchang e becomes the key issue in current computer technology. At the moment we are on the brink of the second Web generation called Semantic Web or Knowledgeable Web. Given the increasing amount of information available on-line, this kind of sup port is becoming more important day by day. The main idea of the proposed approach is to replace interface models by appropr iate ontologies. Some parts of these ontologies will be available from the Inter net; the other parts will be built by developers. As a result of the Semantic We b development we will have increasing the number of ontologies formally describe d in the Internet. The terminology and content of these ontologies will be inter nationally standardized. Reusing these ontologies will bring down the cost of de velopment and improve the quality of user interface. The parts of a user interface model are-a domain ontology model, a dialog ontol ogy model, presentation ontology model, "business- logic" variable ontology mod el and correspondences between these parts. Thus, the user interface development based on ontologies is an evolution of th e model-based approach, where appropriate ontologies are used instead of models .

Ontologies for Software Project Management: A Review

Software Project Management is a knowledge intensive process that can benefit substantially from ontology development and ontology engineering. Ontology development could facilitate or improve substantially the software development process through the improvement of knowledge management, the increase of software and artefacts reusability, and the establishment of internal consistency within project management processes of various phases of software life cycle. A large number of ontologies have been developed attempting to address various software engineering aspects, such as requirements engineering, components reuse, domain modelling, etc. In this paper, we present a systematic literature review focusing on software project management ontologies. The literature review, among other, has identified lack of standardization in terminology and concepts, lack of systematic domain modelling and use of ontologies mainly in prototype ontology systems that address rather limited aspects of software project management processes.

Query Through Heterogeneous Ontologies Using Association Matrix

This paper introduces the definition and calculation of the association matrix between ontologies. It uses the association matrix to describe the relations between concepts in different ontologies and uses concept vectors to represent queries; then computes the vectors with the association matrix in order to rewrite queries. This paper proposes a simple method of querying through heterogeneous Ontology using association matrix. This method is based on the correctness of approximate information filtering theory; and it is simple to be implemented and expected to run quite fast. Key words semantic Web - information retrieval - ontology - query - association matrix CLC number TP 391 Foundation item: Supported by the National Natural Science Foundation of China (60373066, 60303024), National Grand Fundamental Research 973 Program of China (2002CB312000) and National Research Foundation for the Doctoral Program of Higher Education of China (20020286004)Biography: KANG Da-zhou (1980-), male, Master candidate, research direction: Semantic Web, knowledge representation on the Web.

Concept Approximation between Fuzzy Ontologies

Fuzzy ontologics are efficient tools to handle fuzzy and uncertain knowledge on the semantic web; but there are heterogeneity problems when gaining interoperability among different fuzzy ontologies. This paper uses concept approximation between fuzzy ontologies based on instances to solve the heterogeneity problems. It firstly proposes an instance selection technology based on instance clustering and weighting to unify the fuzzy interpretation of different ontologies and reduce the number of instances to increase the efficiency. Then the paper resolves the problem of computing the approximations of concepts into the problem of computing the least upper approximations of atom concepts. It optimizes the search strategies by extending atom concept sets and defining the least upper bounds of concepts to reduce the searching space of the problem. An efficient algorithm for searching the least upper bounds of concept is given.

Revision of stratified OWL ontologiesbased on integer linear programming

To revise stratified web ontology language(OWL)ontologies,the kernel revision operator is extended by defining novel conflict stratification and the incision function based on integer linear programming(ILP).The ILP-based model considers an optimization problem of minimizing a linear objective function which is suitable for selecting the minimal number of axioms to remove when revising ontologies.Based on the incision function,a revision algorithm is proposed to apply ILP to all minimal incoherence-preserving subsets(MIPS).Although this algorithm can often find a minimal number of axioms to remove,it is very time-consuming to compute MIPS.Thus,an adapted revision algorithm to deal with unsatisfiable concepts individually is also given.Experimental results reveal that the proposed ILP-based revision algorithm is much more efficient than the commonly used algorithm based on the hitting set tree.In addition,the adapted algorithm can achieve higher efficiency,while it may delete more axioms.

Subsumption Checking between Concept Queries in Different Ontologies Based on Mutual Instances

This paper proposes a checking method based on mutual instances and discusses three key problems in the method： how to deal with mistakes in the mutual instances and how to deal with too many or too few mutual instances. It provides the checking based on the weighted mutual instances considering fault tolerance, gives a way to partition the large-scale mutual instances, and proposes a process greatly reducing the manual annotation work to get more mutual instances. Intension annotation that improves the checking method is also discussed. The method is practical and effective to check subsumption relations between concept queries in different ontologies based on mutual instances.

A Process for Extracting Non-Taxonomic Relationships of Ontologies from Text

Manual construction of ontologies by domain experts and knowledge engineers is an expensive and time consuming task so, automatic and/or semiautomatic approaches are needed. Ontology learning looks for identifying ontology elements like non-taxonomic relationships from information sources. These relationships correspond to slots in a frame-based ontology. This article proposes an initial process for semiautomatic extraction of non-taxonomic relationships of ontologies from textual sources. It uses Natural Language Processing (NLP) techniques to identify good candidates of non-taxonomic relationships and a data mining technique to suggest their possible best level in the ontology hierarchy. Once the extraction of these relationships is essentially a retrieval task, the metrics of this field like recall, precision and f-measure are used to perform evaluation.