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Journal ArticleDOI

QAPD: an ontology-based question answering system in the physics domain

TLDR
QAPD, an ontology-based QA system applied to the physics domain, which integrates natural language processing, ontologies and information retrieval technologies to provide informative information for users, is presented and inferring schema mapping method is proposed, which uses the combination of semantic and syntactic information, and attribute-based inference to transform users’ questions into ontological knowledge base query.
Abstract
The tremendous development in information technology led to an explosion of data and motivated the need for powerful yet efficient strategies for knowledge discovery. Question answering (QA) systems made it possible to ask questions and retrieve answers using natural language queries. In ontology-based QA system, the knowledge-based data, where the answers are sought, have a structured organization. The question-answer retrieval of ontology knowledge base provides a convenient way to obtain knowledge for use. In this paper, QAPD, an ontology-based QA system applied to the physics domain, which integrates natural language processing, ontologies and information retrieval technologies to provide informative information for users, is presented. This system allows users to retrieve information from formal ontologies using input queries formulated in natural language. We proposed inferring schema mapping method, which uses the combination of semantic and syntactic information, and attribute-based inference to transform users' questions into ontological knowledge base query. In addition, a novel domain ontology for physics domain, called EAEONT, is presented. Relevant standards and regulations have been utilized extensively during the ontology building process. The original characteristic of system is the strategy used to fill the gap between users' expressiveness and formal knowledge representation. This system has been developed and tested on the English language and using an ontology modeling the physics domain. The performance level achieved enables the use of the system in real environments.

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Citations
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Journal ArticleDOI

A literature review on question answering techniques, paradigms and systems

TL;DR: This study aims at identifying QA techniques, tools and systems, as well as the metrics and indicators used to measure these approaches for QA systems and also to determine how the relationship between Question Answering and natural language processing is built.
Journal ArticleDOI

Review and Trend Analysis of Knowledge Graphs for Crop Pest and Diseases

TL;DR: The challenges and important problems of diseases and pest knowledge graph are summarized and the prospect of knowledge graph is forecasted according to the key points and difficulties of current knowledge graph research.
Proceedings ArticleDOI

ADANS: An agriculture domain question answering system using ontologies

Manmita Devi, +1 more
TL;DR: This paper presents a QA system on agriculture domain, the ADANS, to answer queries given in natural language using a combination of Natural Language Processing (NLP) and semantic web technologies.
Proceedings ArticleDOI

Towards a Framework for Closed-Domain Question Answering in Italian

TL;DR: A preliminary Question Answering framework for closed-domains, like Cultural Heritage, that exploits a variety of NLP methods for the Italian language to help the understanding of user's questions and the extraction of precise answers from textual passages contained into documents.
Journal ArticleDOI

A Study of Optimizing Search Engine Results Through User Interaction

TL;DR: A storage-free approach based on individual users operating on different search topics that can achieve optimal linear time in generating personalized search results and avoid personal privacy and storage space issues.
References
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Book

Introduction to Information Retrieval

TL;DR: In this article, the authors present an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections.
Proceedings Article

ROUGE: A Package for Automatic Evaluation of Summaries

TL;DR: Four different RouGE measures are introduced: ROUGE-N, ROUge-L, R OUGE-W, and ROUAGE-S included in the Rouge summarization evaluation package and their evaluations.
Book

Introduction to Magnetic Materials

TL;DR: In this paper, the authors present materials at the practical rather than theoretical level, allowing for a physical, quantitative, measurement-based understanding of magnetism among readers, be they professional engineers or graduate-level students.

Ontology Development 101: A Guide to Creating Your First Ontology

TL;DR: An ontology defines a common vocabulary for researchers who need to share information in a domain that includes machine-interpretable definitions of basic concepts in the domain and relations among them.
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