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Development and Alignment of a Domain-Specific Ontology for Question Answering

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TLDR
The aligned ontology was used to semantically annotate original data obtained from the tourism web sites and natural language questions and its alignment with the upper ontologies - WordNet and SUMO is described.
Abstract
With the appearance of Semantic Web technologies, it becomes possible to develop novel, sophisticated question answering systems, where ontologies are usually used as the core knowledge component. In the EU-funded project, QALL-ME, a domain-specific ontology was developed and applied for question answering in the domain of tourism, along with the assistance of two upper ontologies for concept expansion and reasoning. This paper focuses on the development of the QALL-ME ontology in the tourism domain and its alignment with the upper ontologies - WordNet and SUMO. The design of the ontology is presented in the paper, and a semi-automatic alignment procedure is described with some alignment results given as well. Furthermore, the aligned ontology was used to semantically annotate original data obtained from the tourism web sites and natural language questions. The storage schema of the annotated data and the data access method for retrieving answers from the annotated data are also reported in the paper.

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Covering the semantic space of tourism: an approach based on modularized ontologies

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The QALL-ME Framework: A specifiable-domain multilingual Question Answering architecture ⁎ ☆

TL;DR: This paper presents the QALL-ME Framework, a reusable architecture for building multi- and cross-lingual Question Answering (QA) systems working on structured data modelled by an ontology, and presents a running example to clarify how the framework processes questions.
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Marketing decision support using Artificial Intelligence and Knowledge Modeling: application to tourist destination management

TL;DR: Advanced data analysis, neural networks and knowledge representation technologies are brought together towards an intelligent information system for tourist destination marketing, showing that the intelligent system was able to assist users who are not experts in analysis to solve typical destination marketing problems.
References
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Journal ArticleDOI

WordNet : an electronic lexical database

Christiane Fellbaum
- 01 Sep 2000 - 
TL;DR: The lexical database: nouns in WordNet, Katherine J. Miller a semantic network of English verbs, and applications of WordNet: building semantic concordances are presented.
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Foundations of Statistical Natural Language Processing

TL;DR: This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear and provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations.
Journal ArticleDOI

CYC: a large-scale investment in knowledge infrastructure

TL;DR: The fundamental assumptions of doing such a large-scale project are examined, the technical lessons learned by the developers are reviewed, and the range of applications that are or soon will be enabled by the technology is surveyed.
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