Ontology (information science)

About: Ontology (information science) is a research topic. Over the lifetime, 57081 publications have been published within this topic receiving 869118 citations. The topic is also known as: vocabulary & computational ontology.

Coupling of wordnet entries for ontology mapping using virtual documents

Abstract: Facilitating information exchange is a crucial service for ontology-based knowledge systems. This can be achieved by the mapping of two heterogenous ontologies. Many mapping frameworks utilize language-based knowledge resources such as WordNet. By coupling all ontology concepts to a corresponding entry in WordNet, one can quantify the lexical relatedness of any two ontology concepts. However, coupling the correct entry is a difficult task due to the ambiguous nature of names. Coupling the wrong entries hence yields similarity values that do not correctly express the relatedness of two given concepts, resulting in a poor performance of the overall mapping framework. This paper proposes an approach for the more accurate coupling of ontology concepts with their corresponding WordNet entries. The basis of the proposed approach is the creation of separate virtual documents representing the different ontology concepts and WordNet entries and coupling these according to their document similarities. The extent of improvements using this approach are evaluated using a data set originating from the Ontology Alignment Evaluation Initiative (OAEI). Furthermore, the performance of a framework using our approach is demonstrated using the results of the OAEI 2011 competition.

A Study on Intelligent User-Centric Logistics Service Model Using Ontology

Abstract: Much research has been undergone in the smart logistics environment for the prompt delivery of the product in the right place at the right time. Most of the services were based on time management, routing technique, and location based services. The services in the recent logistics environment aim for situation based logistics service centered around the user by utilizing various information technologies such as mobile devices, computer systems, and GPS. This paper proposes a smart logistics service model for providing user-centric intelligent logistics service by utilizing smartphones in a smart environment. We also develop an OWL based ontology model for the smart logistics for the better understanding among the context information. In addition to basic delivery information, the proposed service model makes use of the location and situation information of the delivery vehicle and user, to draw the route information according to the user’s requirement. With the increase of internet usage, the real-time situations are received which helps to create a more reliable relationship, owing to the Internet of Things. Through this service model, it is possible to engage in the development of various IT and logistics convergence services based on situation information between the deliverer and user which occurs in real time.

Ontology-based Aspect Extraction for an Improved Sentiment Analysis in Summarization of Product Reviews

Abstract: Current approaches in aspect-based sentiment analysis ignore or neutralize unhandled issues emerging from the lexicon-based scoring (i.e., SentiWordNet), whereby lexical sentiment analysis only classifies text based on affect word presence and word count are limited to these surface features. This is coupled with considerably low detection rate among implicit concepts in the text. To address this issues, this paper proposed the use of ontology to i) enhance aspect extraction process by identifying features pertaining to implicit entities, and ii) eliminate lexicon-based sentiment scoring issues which, in turn, improve sentiment analysis and summarization accuracy. Concept-level sentiment analysis aims to go beyond word-level analysis by employing ontologies which act as a semantic knowledge base rather than the lexicon. The outcome is an Ontology-Based Product Sentiment Summarization (OBPSS) framework which outperformed other existing summarization systems in terms of aspect extraction and sentiment scoring. The improved performance is supported by the sentence-level linguistic rules applied by OBPSS in providing a more accurate sentiment analysis.

An integrated, ontology-based agricultural information system

Abstract: This paper proposes an integrated, ontology-based agricultural information system (AIS) to provide all-round and precise information for efficiently guiding farmers and agri-professionals to conduct agricultural processing. Since the existing independent AIS platforms can only offer specific but incomplete agricultural information service, aiming at this issue, the newly proposed AIS system employs ontology techniques, including RDF-based representation and semantic reasoning, to integrate the index information provided by all involved independent agricultural information platforms. As a result, this newly proposed AIS system can provide users with integrated and accurate response information. Through a realistic case study and relevant experiments, it is clear that the accuracy ratio and integrity ratio of response information offered by this ontology-based integrated AIS can be enhanced to a great extent. In summary, not only agri-professionals, but also farmers, who might not understand information ret...