Ontology alignment through argumentation

Currently, the majority of matchers are able to establish simple correspondences between entities, but are not able to provide complex alignments. Furthermore, the resulting alignments do not contain additional information on how they were extracted and formed. Not only it becomes hard to debug the alignment results, but it is also difficult to justify correspondences. We propose a method to generate complex ontology alignments that captures the semantics of matching algorithms and human-oriented ontology alignment definition processes. Through these semantics, arguments that provide an abstraction over the specificities of the alignment process are generated and used by agents to share, negotiate and combine correspondences. After the negotiation process, the resulting arguments and their relations can be visualized by humans in order to debug and understand the given correspondences.(undefined

Review implementation of linguistic approach in schema matching

Research related schema matching has been conducted since last decade. Few approach related schema matching has been conducted with various methods such as neuron network, feature selection, constrain based, instance based, linguistic, and so on. Some field used schema matching as basic model such as e-commerce, e-business and data warehousing. Implementation of linguistic approach itself has been used a long time with various problem such as to calculated entity similarity values in two or more schemas. The purpose of this paper was to provide an overview of previous studies related to the implementation of the linguistic approach in the schema matching and finding gap for the development of existing methods. Futhermore, this paper focused on measurement of similarity in linguistic approach in schema matching

Survey: Models and Prototypes of Schema Matching

Schema matching is critical problem within many applications to integration of data/information, to achieve interoperability, and other cases caused by schematic heterogeneity. Schema matching evolved from manual way on a specific domain, leading to a new models and methods that are semi-automatic and more general, so it is able to effectively direct the user within generate a mapping among elements of two the schema or ontologies better. This paper is a summary of literature review on models and prototypes on schema matching within the last 25 years to describe the progress of and research chalenge and opportunities on a new models, methods, and/or prototypes

OLA in the OAEI 2007 evaluation contest

djoufak2007aInternational audienceSimilarity has become a classical tool for ontology confrontation motivated by alignment, mapping or merging purposes. In the definition of an ontologybased measure one has the choice between covering a single facet (e.g., URIs, labels, instances of an entity, etc.), covering all of the facets or just a subset thereof. In our matching tool, OLA, we had opted for an integrated approach towards similarity, i.e., calculation of a unique score for all candidate pairs based on an aggregation of all facet-wise comparison results. Such a choice further requires effective means for the establishment of importance ratios for facets, or weights, as well as for extracting an alignment out of the ultimate similarity matrix. In previous editions of the competition OLA has relied on a graph representation of the ontologies to align, OL-graphs, that reflected faithfully the syntactic structure of the OWL descriptions. A pair of OL-graphs was exploited to form and solve a system of equations whose approximate solutions were taken as the similarity scores. OLA2 is a new version of OLA which comprises a less integrated yet more homogeneous graph representation that allows similarity to be expressed as graph matching and further computed through matrix multiplying. Although OLA2 lacks key optimization tools from the previous one, while a semantic grounding in the form of WORDNET engine is missing, its results in the competition, at least for the benchmark test suite, are perceivably better

Improving Document Exchanges in the Supply Chain

Abstract. In order to help businesses to communicate fruitfully, we present a solution based on ontology alignment for integrating business documents. We focus on detecting and resolving semantic conflicts encountered during the integration process due to different terminologies used in xCBL, cXML and RosettaNet. Our contribution is to benefit from research in the ontology alignment area and considered as empirical study to test if alignment solution can overcome the heterogeneity problems between business systems. As case study, we apply alignment on purchase order ontologies, a common task of the supply chain

Tích hợp ontology với tiếp cận lý thuyết đồng thuận

The reuse of ontology has been an important factor in developing shared knowledge on the Semantic Web. However, this cannot completely reduce conflict potentials in knowledge bases. In the ontology integration process on the concept level, we need to determine the domain and range ofproperties of integrating ontologies. This paper presents an algorithm for ontology integration on concept level based on the consensus theory and an evaluation function of a similarity measure between concepts in its hierarchical structure. This paper also proves that the consensus theory is a useful tool for building collective knowledge from different sources.World Wide Web (WWW) phát triển nhằm cho phép con người có thể chia sẻ thông tin với nhau thông qua môi trường phân tán. Nhằm đáp ứng nhu cầu sử dụng dịch vụ ngày càng cao thì dịch vụ Web là nơi hỗ trợ khả năng tương tác giữa các ứng dụng trên các máy tính khác nhau thông qua môi trường Internet và sự gắn kết giữa chúng được mô tả bằng ngôn ngữ XML. Cùng sự phát triển của Web ngữ nghĩa với mục đích nâng cao hiệu quả của Web hiện tại, số lượng các Ontology do các cá nhân, tổ chức nghiên cứu, doanh nghiệp tạo ra ngày càng trở nên phong phú và đa dạng hơn. Tích hợp các Ontology từ các nguồn trên nhằm mang lại lợi ích trong quá trình hợp tác, đồng thời khám phá ra các dịch vụ Web ngữ nghĩa phù hợp với yêu cầu ban đầu của người sử dụng. Có nhiều cách tiếp cận cho bài toán tích hợp ontology, bài báo tập trung nghiên cứu theo hướng tiếp cận thông minh trong tích hợp ontology bằng cách sử dụng lý thuyết đồng thuận – một phương pháp tiếp cận mới giúp quá trình khám phá, biên tập dịch vụ Web một cách tự động và thông minh hơn

LDM: Link Discovery Method for new Resource Integration

International audienceIn this paper we address the problem of resource discovery in the Linked Open Data cloud (LOD) where data described by different schemas is not always linked. We propose an approach that allows discovery of new links between data. These links can help to match schemas that are conceptually relevant with respect to a given application domain. Furthermore, these links can be exploited during the querying process in order to combine data coming from different sources. In this approach we exploit the semantic knowledge declared in different schemas in order to model: (i) the influences between concept similarities, (ii) the influences between data similarities, and (iii) the influences between data and concept similarities. The similarity scores are computed by an iterative resolution of two non linear equation systems that express the concept similarity computation and the data similarity computation. The proposed approach is illustrated on scientific publication data.Dans ce papier nous nous intéressons au problème de découverte de resource dans le LOD (Linked Open Data), dans lequel les données décrites conformément à différents schémas ne sont pas toujours liées. Les liens sémantiques entre données peuvent aider à la recherche de correspondances entre schémas. De plus ces liens peuvent être exploités au moment des requêtes pour combiner des données décrites dans différentes sources. Dans cette approche, nous exploitons la sémantique des schémas de façon à modéliser : (1) les influences entre similarités de concept, (2) les influences entre similarités de données. Les scores de similarité sont calculés en résolvant itérativement deux systèmes d'équations représentant le calcul des similarités conceptuelles et le calcul des similarités entre données. L'approche est illustrée en utilisant le domaine des publications scientifiques

Argumentation over Ontology Correspondences in MAS

laera2007aInternational audienceIn order to support semantic interoperation in open environments, where agents can dynamically join or leave and no prior assumption can be made on the ontologies to align, the different agents involved need to agree on the semantics of the terms used during the interoperation. Reaching this agreement can only come through some sort of negotiation process. Indeed, agents will differ in the domain ontologies they commit to; and their perception of the world, and hence the choice of vocabulary used to represent concepts. We propose an approach for supporting the creation and exchange of different arguments, that support or reject possible correspondences. Each agent can decide, according to its preferences, whether to accept or refuse a candidate correspondence. The proposed framework considers arguments and propositions that are specific to the matching task and are based on the ontology semantics. This argumentation framework relies on a formal argument manipulation schema and on an encoding of the agents' preferences between particular kinds of arguments

Linking Moving Object Databases with Ontologies

This work investigates the supporting role of ontologies for supplementing the information contained in moving object databases. Details of the spatial representation as well as the sensed location of moving objects are frequently stored within a database schema. However, this knowledge lacks the semantic detail necessary for reasoning about characteristics that are specific to each object. Ontologies contribute semantic descriptions for moving objects and provide the foundation for discovering similarities between object types. These similarities can be drawn upon to extract additional details about the objects around us. The primary focus of the research is a framework for linking ontologies with databases. A major benefit gained from this kind of linking is the augmentation of database knowledge and multi-granular perspectives that are provided by ontologies through the process of generalization. Methods are presented for linking based on a military transportation scenario where data on vehicle position is collected from a sensor network and stored in a geosensor database. An ontology linking tool, implemented as a stand alone application, is introduced. This application associates individual values from the geosensor database with classes from a military transportation device ontology and returns linked value-class pairs to the user as a set of equivalence relations (i.e., matches). This research also formalizes a set of motion relations between two moving objects on a road network. It is demonstrated that the positional data collected from a geosensor network and stored in a spatio-temporal database, can provide a foundation for computing relations between moving objects. Configurations of moving objects, based on their spatial position, are described by motion relations that include isBehind and inFrontOf. These relations supply a user context about binary vehicle positions relative to a reference object. For example, the driver of a military supply truck may be interested in knowing what types of vehicles are in front of the truck. The types of objects that participate in these motion relations correspond to particular classes within the military transportation device ontology. This research reveals that linking a geosensor database to the military transportation device ontology will facilitate more abstract or higher-level perspectives of these moving objects, supporting inferences about moving objects over multiple levels of granularity. The details supplied by the generalization of geosensor data via linking, helps to interpret semantics and respond to user questions by extending the preliminary knowledge about the moving objects within these relations