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Abstract: Publicly available text-based documents (e.g. news, meeting transcripts) are a very important source of knowledge for organizations and individuals. These documents refer domain entities such as persons, places, professional positions, decisions, actions, etc. Querying these documents (instead of browsing, searching and finding) is a very relevant task for any person in general, and particularly for professionals dealing with intensive knowledge tasks. Querying text-based documents’ data, however, is not supported by common technology. For that, such documents’ content has to be explicitly and formally captured into knowledge base facts. Making use of automatic NLP processes for capturing such facts is a common approach, but their relatively low precision and recall give rise to data quality problems. Further, facts existing in the documents are often insufficient to answer complex queries and, therefore, it is often necessary to enrich the captured facts with facts from third-party repositories (e.g. public LOD, private IS databases). This paper describes the adopted process to identify what data is currently missing from the knowledge base repository and which is desirable to collect from external repositories. The proposed process aims to foster and is driven by OWL DL inference-based instance (ABox) classification, which is supported by the constraints of the TBox.
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Abstract: Agent-based Ontology Alignment Negotiation processes aims to generate an alignment through the interaction of two or more agents. When these agents exploit different matching services they can reach incompatible alignments, giving rise to conflicts hence the need to engage in a negotiation to achieve consensus. This consensus is sounder as more conflicts are correctly solved. In this paper, a Relaxation-based approach for Agent-based Ontology Matching Negotiation is explored and compared with the MbA/FDO argument-based approach. The limitations of the original Relaxation approach are addressed and modifications are proposed that increase the circumstances under which conflict resolution may occur, thus generating sounder alignments.
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Abstract: Publicly available text-based documents (e.g. news, meeting transcripts) are a very important source of knowledge, especially for organizations. These documents refer domain entities such as persons, places, professional positions, decisions and actions. Querying these documents (instead of browsing, searching and finding) is a very relevant task for any person in general, and particularly for professionals dealing with intensive knowledge tasks. Querying text-based documents’ data, however, is not supported by common technology. For that, such documents’ content has to be explicitly and formally captured as facts into a knowledge base. Making use of automatic NLP processes for capturing such facts is a common approach, but their relatively low precision and recall give rise to data quality problems. Further, facts existing in the documents are often insufficient to answer complex queries, thus the need to enrich the captured facts with facts from third-party repositories (e.g. public LOD). This paper describes the adopted process to clean, populate and enrich a knowledge base repository that is further exploited to answer complex queries. This process is triggered by a previous NLP parsing process and conducted by the (rich) ontology describing such repository.
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Abstract: Agents participating in a negotiation dialogue may use argumentation to support their position, hence achieving a better agreement. The Extensible Argumentation Framework (EAF) provides modularity and extensibility features that facilitates the adoption of argumentation by agents in MAS. In order to emphasize the EAF potential and applicability, this paper proposes an argument-based negotiation process grounded on the EAF adoption. Experiments demonstrate advantages of the proposal respecting conflict resolution and accuracy of the agreement.
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Abstract: Open ontology-described repositories are becoming very common in the web and in enterprises. These repositories are well-suited to answer complex queries, but in order to fully exploit their potential, the queries should be written in a user-demand basis, and not in a traditional static approach by software developers. Hence, the users are required (i) to know the underlying ontology(ies) and/to (ii) write formal queries. Yet, the users often lack such requirements. In this paper we first describe the observations made during manual complex querying process and present a systematization of the users’ support wish list for building complex queries. Based on this systematization we propose an extended set of functionalities for a user-supporting system. Finally, we demonstrate their application in a walk-through example and their implementation within a prototype.
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Abstract: Although ontologies are used to describe a specific domain of interest, they can grow in size exponentially, compromising their usage. Furthermore, current ontology engineering tools do not effectively support the data/information visualization and navigation described through large ontologies. To address these issues, we claim that the experience and results of navigating/browsing ontology-described data can profit from the modularization of the ontologies underlying the repositories. For that, we propose the I3OM process that facilitates ontology-oriented navigation and contextualized information retrieval by combining different ontology modularization techniques into an iterative, incremental and interactive process.
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Abstract: Communication between agents adopting different ontologies and with no prior knowledge of the other relies on agents’ ability to match (or align) their ontologies in run-time. Because agents pursue different goals, they might also have different perspectives and preferences regarding the ontology matching process. To address conflicts arising from the matching process, agents engage in negotiation processes that lead them to a common and acceptable agreement. In literature, two kinds of ontology matching negotiation approaches can be found: (i) relaxation-based approaches and (ii) argument-based approaches. In this paper we survey these approaches in order to further analyze and suggest their combination based on three identified dimensions.
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Abstract: Argumentation frameworks which are abstract are suitable for the study of independent properties of any specific aspect (e.g. arguments sceptical and credulous admissible) that are relevant for any argumentation context. However, its direct adoption on specific application contexts requires dealing with questions such as the argument structure, the argument categories, the conditions under which an attack/support is established between arguments, etc. This paper presents a generic argumentation framework which comprehends a conceptualization layer to capture the expressivity and semantics of the argumentation data employed in a specific context and simplifies its adoption by applications. The conceptualization layer together with the defined argument structure is exploited to automatically derive the attack and support relationships between arguments.
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Abstract: 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.
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Abstract: We propose a lightweight technological system for managing user’s documents according to multiple classification dimensions. The core of the proposal is the application of {ALC-expressive} ontologies for capturing the multi-property-based classification of documents. The ontology is then responsible for representing (i) the properties that serve for the document classification (e.g. authors, subjects, types), and (ii) the classes of documents specified based on the properties’ values of the documents. Once the ontology is populated with data captured from the documents via parsers/analyzers, an inference engine logically classify documents according to the classes.
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Abstract: Agent technology has been successfully applied to the Electronic Commerce domain, but the diversity of the involved actors leads to different conceptualizations of the needs and capabilities, giving rise to semantic incompatibilities between them. It is hard to find two agents using precisely the same vocabulary. They usually have a heterogeneous private vocabulary defined in their own private ontology. In order to provide help in the conversation among different agents, we are proposing what we call ontology-services to facilitate agents’ interoperability. More specifically, this work presents a multi-agent market simulator with ontology services. The system includes agents that provide services that allow other agents to communicate with each other in order to reach an agreement, ensuring that both parties are able to understand the terms of negotiation.
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Abstract: Agents embedded on open, dynamic and decentralized environments adopt different ontologies to describe their domain of discourse. Yet, agents have no prior knowledge of the other agents with whom they will interact. Therefore, a consistent and compatible communication relies on the agents’ ability to reconcile in run-time the vocabulary used in their ontologies whose result is a set of correspondences. Since each party might have its own perspective about what are the best correspondences, conflicts arise. To address such conflicts, it is envisaged as a suitable approach that agents adopt the generic argument-based negotiation process presented in [1]. A critical issue of that process concerns the arguments generation process according to the argumentation framework that it relies on. In this paper it is proposed an automatic process to generate arguments regarding the ontologies reconciliation through semantic interpretations of third party generated correspondences.
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Abstract: Argumentation frameworks which are abstract are suitable for the study of independent properties of any specific aspect (e.g. arguments sceptical and credulous admissible) that are relevant for any argumentation context. However, its direct adoption on specific application contexts requires dealing with questions such as the argument structure, the argument categories, the conditions under which an attack/support is established between arguments, etc. This paper presents a generic argumentation framework which comprehends a conceptualization layer to capture the expressivity and semantics of the argumentation data employed in a specific context and simplifies its adoption by applications.
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Abstract: Agents participating in a negotiation dialogue may use argumentation to support their position, hence achieving a better agreement. The Extensible Argumentation Framework (EAF) provides modularity and extensibility features that facilitates its adoption by agents in MAS. In order to emphasize the EAF potential and applicability, this paper proposes an argument-based negotiation process grounded on the EAF adoption.
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Abstract: For a successful communication, autonomous entities (e.g. agents, web services, peers) must reconcile vocabulary used in their ontologies. The result is a set of mappings between ontology entities. Since each party might have its own perspective about what are the best mappings, conflicts will arise. Toward a mapping consensus building between information exchanging parties, this paper proposes an approach based on a formal argumentation framework, whose existing ontology matching algorithms generate the mappings, which are further interpreted into semantic arguments employed during the argumentation. The proposal models a mutual dependency between the mappings and arguments, which goes beyond the state of the art in argumentation-based ontology alignment negotiation, better reflecting the requirements of the task.
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Abstract: This paper proposes a semantic information integration approach for agent-based electronic markets based on ontology-based technology, improved by the application and exploitation of the trust relationships captured by the social networks. We intent face the problem of the growth of e-commerce using software agents to support both customers and suppliers in buying and selling products. The diversity of the involved actors leads to different conceptualizations of the needs and capabilities, giving rise to semantic incompatibilities between them. It is hard to find two agents using precisely the same vocabulary. They usually have a heterogeneous private vocabulary defined in their own private ontology. In order to provide help in the conversation among different agents, we are proposing what we call ontology-services to facilitate agents’ interoperability. More specifically, this work proposes an ontology-based information integration approach, exploiting the ontology mapping paradigm, by aligning consumer needs and the market capacities, in a semi-automatic mode, improved by the application and exploitation of the trust relationships captured by the social networks.
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Abstract: State-of-the-art ontology matching systems rely on the combination of basic matching techniques but good results are only achieved when processing particular classes of ontologies. Furthermore, they are quite restrictive with respect to their internal configuration, as they are committed to a pre-defined architecture and workflow. Additionally, the skilful selection of matchers and the respective combination and configuration process is difficult and time consuming. Additionally it is hard to test and evaluate. This paper presents a test-bed system that eases the creation of new matching systems. It promotes the reusability, the combination and the configuration of existing matchers, encouraging the development of new matching algorithms able to fill specific open matching gaps exploiting existing methods and algorithms.
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Abstract: This paper describes the architecture of a knowledge management system that exploits social and semantic web technology in order to ease and promote user-centered modeling, evolution, sharing and access to knowledge in distributed and heterogeneous repositories. For that, several knowledge engineering processes are improved in order to exploit social information between users and communities.
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Abstract: Many methods for automatic and semi-automatic ontology alignment have been proposed, but they remain error prone and labor-intensive. This paper describes a novel generic process for evaluating the mappings' confidence value. This process uses rules extracted through inductive machine learning methods from the matching results proposed by others. Further, the precision and recall of the extracted rules are exploited in order to transform each rule into a mathematical formula that generates the mappings' confidence value. Mappings are then classified not as valid or invalid but through a quantitative confidence value that can be easily managed during the alignment process.
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Abstract: An approach to achieve ontology mapping agreements between autonomous entities is presented. In the proposed approach, entities relax their mapping requirements based on the reciprocal behavior from others. The process and protocol for agreement are presented.
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Abstract: Ontology mapping negotiation aims to achieve consensus among real-world entities about the process of transforming information between different ontologies. This paper describes a novel ontology mapping negotiation approach, based on the categorization of semantic bridges according to their confidence and relevance to the interoperability. The semantic bridges are then proposed between two agents in order to derive an ontology mapping agreement. Agents representing the real-world entities are able to achieve consensus based on the re-categorization of semantic bridges. The negotiation process, the intervenients and flow of execution is further described, thus presenting an integrated perspective of the envisaged system.
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Abstract: This paper gives an overview of current semantic web annotation terminology and technology. For this, it focuses on the systematization of existing terms according to different contexts, projects and application areas. In order to present a clear definition of terms, scientific and commercial projects are related to the processes each one is expected to support in the semantic web annotation tasks.
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Abstract: Ontology mapping negotiation aims to achieve consensus among real-world entities about the process of transforming information between different models (ontologies). This paper describes a novel approach for ontology mapping negotiation, in which agents representing the real-world entities are able to achieve consensus among agents, about the mapping rules defined between two different ontologies. The proposed approach is based on utility functions that evaluate the confidence in a certain mapping rule. According to the confidence value, the mapping rule is accepted, rejected or negotiated. Since the negotiation process requires relaxation of the confidence value, a meta-utility function is applied, evaluating the effort made in relaxing (increasing) the confidence value, so that the mapping rule might be accepted. This convergence value is further applied by each agent in the evaluation of the global agreement.
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