An approach for incremental knowledge acquisition from text

Ruiz-Sánchez, Juana Marı́a; Valencia‐García, Rafael; Fernández-Breis, Jesualdo Tomás; Martı́nez-Béjar, Rodrigo; Compton, Paul

doi:10.1016/s0957-4174(03)00008-3

Cited by 25 publications

(5 citation statements)

References 9 publications

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“…The screenshot shows the user interface when the Service Discovery panel is clicked. The service request in the above natural language is translated into an OWL-S-based formal model of query tree that is easy for both user understanding and machine processing, by employing a knowledge acquisition tool that is able to transform the natural language into a formal ontology (Ruiz-Sanchez et al, 2003). The right window shown in the screenshot displays the formal model of query tree, which may be edited and modified by the user manually.…”

Section: Semantic Discovery Of Manufacturing Service Across Virtual Ementioning

confidence: 99%

A reputation-based peer-to-peer architecture for semantic service discovery in distributed manufacturing environments

Zhang

Cai

et al. 2012

Concurrent Engineering

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The rapidly increasing volume of today's global manufacturing resources is demanding new approaches for resource location or discovery in distributed manufacturing environments. This article presents an ontology-based service-oriented peer-to-peer architecture for semantic discovery of manufacturing services across virtual enterprises in distributed manufacturing environments. Each enterprise exhibits as a peer that publishes sharable manufacturing services through its private service registry. The peers sharing similar ontological interests through ontological directory are clustered together, and the most reputed peer is elected as the super peer through multicriteria decision making among related trust parameters. All super peers form a reputed distributed hash table-based structured peer-to-peer overlay, and the leaf peers are communicated with and controlled by respective super peers. Then, a manufacturing service request can be first routed to the suitable super peer through structured indexing and further to its leaf peer through client/server communication, thus supporting efficient service discovery. The case study of the prototype system is presented to validate the applicability of the proposed approach for industrial application.

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Section: Semantic Discovery Of Manufacturing Service Across Virtual Ementioning

confidence: 99%

A reputation-based peer-to-peer architecture for semantic service discovery in distributed manufacturing environments

Zhang

Cai

et al. 2012

Concurrent Engineering

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“…The sequence of the steps our system takes to achieve the goal is as follows: Query analysis (see Figure 7): At first, the system processes and interprets the user request by translating it into an internal goal-ontology model. The 'customer agent' uses KAText (Ruiz-Sa´nchez et al, 2003), which is able to transform a natural-language sentence into a lightweight ontology. Users can also input their wishes by directly setting up an ontology model with their goal.…”

Section: Case Studymentioning

confidence: 99%

Applying intelligent agents and semantic web services in eGovernment environments

et al. 2011

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The increasing volume of eGovernment-related services is demanding new approaches for service integration and interoperability in this domain. Semantic web (SW) technologies and applications can leverage the potential of eGovernment service integration and discovery, thus tackling the problems of semantic heterogeneity characterizing eGovernment information sources and the different levels of interoperability. eGovernment services will therefore be semantically described in the foreseeable future. In an environment with semantically annotated services, software agents are essential as the entities responsible for exploiting the semantic content in order to automate some tasks, and so enhance the user's experience. In this paper, we present a framework that provides a seamless integration of semantic web services and intelligent agents technologies by making use of ontologies to facilitate their interoperation. The proposed framework can assist in the development of powerful and flexible distributed systems in complex, dynamic, heterogeneous, unpredictable and open environments. Our approach is backed up by a proof-of-concept implementation, where the breakthrough of integrating disparate eGovernment services has been tested.

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“…For example, Ontology Learning or KAT (Knowledge Acquisition from Text) aims to extract concepts of a specific domain and taxonomic relations between concepts from text, while the goal of RDC (Relation Detection and Characterization) is to identify relationship between named entities. In the literature [4], there are mainly three kinds of methods for mining relation, including template-based, clustering-based and classificationbased methods [4].…”

Section: Related Workmentioning

confidence: 99%

Mining preorder relation between knowledge units from text

Jiang

et al. 2010

Proceedings of the 2010 ACM Symposium on Applied Computing

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Preorder relation between Knowledge Units (KU) is the precondition for navigation learning. Although possible solutions, existing link mining methods lack the ability of mining preorder relation between knowledge units which are linearly arranged in text. Through the analysis of sample data, we discovered and studied two characteristics of knowledge units: the locality of preorder relation and the distribution asymmetry of domain terms. Based on these two characteristics, a method is presented for mining preorder relation between knowledge units from text documents, which proceeds in three stages. Firstly, the associations between text documents are established according to the distribution asymmetry of domain terms. Secondly, candidate KU-pairs are generated according to the locality of preorder relation. Finally, the preorder relations between KU-pairs are identified by using classification methods. The experimental results show the method can efficiently extract the preorder relation, and reduce the computational complexity caused by the quadratic problem of link mining.

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An approach for incremental knowledge acquisition from text

Cited by 25 publications

References 9 publications

A reputation-based peer-to-peer architecture for semantic service discovery in distributed manufacturing environments

A reputation-based peer-to-peer architecture for semantic service discovery in distributed manufacturing environments

Applying intelligent agents and semantic web services in eGovernment environments

Mining preorder relation between knowledge units from text

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