A lexical approach for taxonomy mapping

Obtaining a useful complete overview of Web-based product information has become difficult nowadays due to the ever-growing amount of information available on online shops. Findings from previous studies suggest that better search capabilities, such as the exploitation of annotated data, are needed to keep online shopping transparent for the user. Annotations can, for example, help present information from multiple sources in a uniform manner. In order to support the product data integration process, we propose an algorithm that can autonomously map heterogeneous product taxonomies from different online shops. The proposed approach uses word sense disambiguation techniques, approximate lexical matching, and a mechanism that deals with composite categories. Our algorithm’s performance compared favorably against two other state-of-the-art taxonomy mapping algorithms on three real-life datasets. The results show that the F1-measure for our algorithm is on average 60% higher than a state-of-the-art product taxonomy mapping algorithm

An information retrieval approach to ontology mapping

In this paper, we present a heuristic mapping method and a prototype mapping system that support the process of semi-automatic ontology mapping for the purpose of improving semantic interoperability in heterogeneous systems. The approach is based on the idea of semantic enrichment, i.e., using instance information of the ontology to enrich the original ontology and calculate similarities between concepts in two ontologies. The functional settings for the mapping system are discussed and the evaluation of the prototype implementation of the approach is reported. \ud \u

Semantic enrichment of knowledge sources supported by domain ontologies

This thesis introduces a novel conceptual framework to support the creation of knowledge representations based on enriched Semantic Vectors, using the classical vector space model approach extended with ontological support. One of the primary research challenges addressed here relates to the process of formalization and representation of document contents, where most existing approaches are limited and only take into account the explicit, word-based information in the document. This research explores how traditional knowledge representations can be enriched through incorporation of implicit information derived from the complex relationships (semantic associations) modelled by domain ontologies with the addition of information presented in documents. The relevant achievements pursued by this thesis are the following: (i) conceptualization of a model that enables the semantic enrichment of knowledge sources supported by domain experts; (ii) development of a method for extending the traditional vector space, using domain ontologies; (iii) development of a method to support ontology learning, based on the discovery of new ontological relations expressed in non-structured information sources; (iv) development of a process to evaluate the semantic enrichment; (v) implementation of a proof-of-concept, named SENSE (Semantic Enrichment kNowledge SourcEs), which enables to validate the ideas established under the scope of this thesis; (vi) publication of several scientific articles and the support to 4 master dissertations carried out by the department of Electrical and Computer Engineering from FCT/UNL. It is worth mentioning that the work developed under the semantic referential covered by this thesis has reused relevant achievements within the scope of research European projects, in order to address approaches which are considered scientifically sound and coherent and avoid “reinventing the wheel”.European research projects - CoSpaces (IST-5-034245), CRESCENDO (FP7-234344) and MobiS (FP7-318452

An explainable data-driven approach to web directory taxonomy mapping

5noThe spread of e-commerce and web applications has fostered the integration of cross-domain business activities. To efficiently retrieve products and services, web directories allow customers to browse multiple-level taxonomies to find specific products or services according to a predefined categorization. Providers need to periodically update web directory lists by aligning in-house taxonomies to domain-specific hierarchies coming from external sources. However, such taxonomy mapping procedures are often semi-automatic and rely on traditional word disambiguation techniques to capture the semantics behind categories and products descriptions. Hence, the flexibility and explainability of the underlying models are quite limited. This paper proposes an automated, explainable approach to web directory taxonomy mapping based on text categorization. It exploits two complementary word-based text representations: a frequency-based representation, which captures syntactic text similarities, and an embedding one, which highlights the underlying semantic relationships among words. Since the proposed solution is purely data-driven, it can be successfully applied to business domains where there is a lack of semantic models. The frequency-based text representation has shown to be particularly suitable for driving the automated taxonomy mapping procedure, whereas the embedding space has been profitably used to provide local explanations of the category assignments.partially_openopenElena Daraio, Luca Cagliero, Silvia Anna Chiusano, Paolo Garza, Giuseppe RicuperoDaraio, Elena; Cagliero, Luca; Chiusano, SILVIA ANNA; Garza, Paolo; Ricupero, Giusepp

Ontology-based services for agents interoperability

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. 2006. Faculdade de Engenharia. Universidade do Port

A Unified Approach for Taxonomy-based Technology Forecasting

For decision makers and researchers working in a technical domain, understanding the state of their area of interest is of the highest importance. For this reason, we consider in this chapter, a novel framework for Web-based technology forecasting using bibliometrics (i.e. the analysis of information from trends and patterns of scientific publications). The proposed framework consists of a few conceptual stages based on a data acquisition process from bibliographic online repositories: extraction of domainrelevant keywords, the generation of taxonomy of the research field of interests and the development of early growth indicators which helps to find interesting technologies in their first phase of development. To provide a concrete application domain for developing and testing our tools, we conducted a case study in the field of renewable energy and in particular one of its subfields: Waste-to-Energy (W2E). The results on this particular research domain confirm the benefit of our approach

Exploring Data Hierarchies to Discover Knowledge in Different Domains

L'abstract è presente nell'allegato / the abstract is in the attachmen

Ontology driven integration platform for clinical and translational research

Semantic Web technologies offer a promising framework for integration of disparate biomedical data. In this paper we present the semantic information integration platform under development at the Center for Clinical and Translational Sciences (CCTS) at the University of Texas Health Science Center at Houston (UTHSC-H) as part of our Clinical and Translational Science Award (CTSA) program. We utilize the Semantic Web technologies not only for integrating, repurposing and classification of multi-source clinical data, but also to construct a distributed environment for information sharing, and collaboration online. Service Oriented Architecture (SOA) is used to modularize and distribute reusable services in a dynamic and distributed environment. Components of the semantic solution and its overall architecture are described