Feature-Wise Opinion Summarization of Consumer Reviews Using Domain Ontology

2021 ◽  
pp. 583-599
Author(s):  
Dushyanthi Vidanagama ◽  
Thushari Silva ◽  
Asoka S. Karunananda
Keyword(s):  
Domain Ontology ◽  
Consumer Reviews ◽  
Opinion Summarization

The Role of Consumer Reviews in Attitude Formation, Communication and Persistence

2010 ◽  
Author(s):  
Georgia Tech ◽  
Samuel Bond ◽  
Talya Miron-Shatz
Keyword(s):  
Attitude Formation ◽  
Consumer Reviews

Know Yourself and Know Your Enemy: An Analysis of Firm Recommendations and Consumer Reviews in a Competitive Environment

MIS Quarterly ◽  
2014 ◽  
Vol 38 (3) ◽  
pp. 635-654 ◽  
Author(s):  
Wael Jabr ◽  
◽  
Zhiqiang (Eric) Zheng ◽  
Keyword(s):  
Competitive Environment ◽  
Consumer Reviews

Automatic Generation of MCQS from Domain Ontology- A Survey

2018 ◽  
Vol 06 (06) ◽  
pp. 99-102
Author(s):  
Sahana Serin V. P. ◽  
Viji Rajendran V.
Keyword(s):  
Automatic Generation ◽  
Domain Ontology

The Method of Power Domain Ontology Construction and Reasoning based on Power Business Platform

2020 ◽  
Vol 9 (2) ◽  
pp. 51-62
Author(s):  
Taekeun Hong ◽  
Kyungho Yu ◽  
Pankoo Kim
Keyword(s):  
Domain Ontology ◽  
Ontology Construction ◽  
Power Domain

Research of semantic retrieval system based on domain-ontology and Lucene

2010 ◽  
Vol 30 (6) ◽  
pp. 1655-1657 ◽  
Author(s):  
Huan WANG ◽  
Rui-zhi SUN
Keyword(s):  
Retrieval System ◽  
Domain Ontology ◽  
Semantic Retrieval

A Methodical Text Mining on a Rationale of Domain Ontology

2019 ◽  
Author(s):  
Bhavan Kumar B ◽  
Vishal B L S R K ◽  
Bhargav K.R. ◽  
Revanth V ◽  
Chintakani Sai Gireesh
Keyword(s):  
Text Mining ◽  
Domain Ontology

The use of a Domain Ontology for the Management of Essential Hypertension (Preprint)

2020 ◽  
Author(s):  
Emma Chavez ◽  
Vanessa Perez ◽  
Angélica Urrutia
Keyword(s):  
Decision Making ◽  
Essential Hypertension ◽  
Medical History ◽  
Medical Records ◽  
Medical Training ◽  
Relevant Information ◽  
Domain Ontology ◽  
Free Text ◽  
Snomed Ct ◽  
History Of

BACKGROUND : Currently, hypertension is one of the diseases with greater risk of mortality in the world. Particularly in Chile, 90% of the population with this disease has idiopathic or essential hypertension. Essential hypertension is characterized by high blood pressure rates and it´s cause is unknown, which means that every patient might requires a different treatment, depending on their history and symptoms. Different data, such as history, symptoms, exams, etc., are generated for each patient suffering from the disease. This data is presented in the patient’s medical record, in no order, making it difficult to search for relevant information. Therefore, there is a need for a common, unified vocabulary of the terms that adequately represent the diseased, making searching within the domain more effective. OBJECTIVE The objective of this study is to develop a domain ontology for essential hypertension , therefore arranging the more significant data within the domain as tool for medical training or to support physicians’ decision making will be provided. METHODS The terms used for the ontology were extracted from the medical history of de-identified medical records, of patients with essential hypertension. The Snomed-CT’ collection of medical terms, and clinical guidelines to control the disease were also used. Methontology was used for the design, classes definition and their hierarchy, as well as relationships between concepts and instances. Three criteria were used to validate the ontology, which also helped to measure its quality. Tests were run with a dataset to verify that the tool was created according to the requirements. RESULTS An ontology of 310 instances classified into 37 classes was developed. From these, 4 super classes and 30 relationships were obtained. In the dataset tests, 100% correct and coherent answers were obtained for quality tests (3). CONCLUSIONS The development of this ontology provides a tool for physicians, specialists, and students, among others, that can be incorporated into clinical systems to support decision making regarding essential hypertension. Nevertheless, more instances should be incorporated into the ontology by carrying out further searched in the medical history or free text sections of the medical records of patients with this disease.

scholarly journals SEOpinion: Summarization and Exploration of Opinion from E-Commerce Websites

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 636
Author(s):  
Alhassan Mabrouk ◽  
Rebeca P. Díaz Redondo ◽  
Mohammed Kayed
Keyword(s):  
Neural Network ◽  
Support Vector Machine ◽  
Cognitive Processing ◽  
Support Vector ◽  
Processing Capacity ◽  
Customer Reviews ◽  
Aspect Extraction ◽  
Descriptive Information ◽  
Opinion Summarization ◽  
Second Phases

Recently, it has been found that e-commerce (EC) websites provide a large amount of useful information that exceed the human cognitive processing capacity. In order to help customers in comparing alternatives when buying a product, previous research authors have designed opinion summarization systems based on customer reviews. They ignored the template information provided by manufacturers, although its descriptive information has the most useful product characteristics and texts are linguistically correct, unlike reviews. Therefore, this paper proposes a methodology coined as SEOpinion (summarization and exploration of opinions) to summarize aspects and spot opinion(s) regarding them using a combination of template information with customer reviews in two main phases. First, the hierarchical aspect extraction (HAE) phase creates a hierarchy of aspects from the template. Subsequently, the hierarchical aspect-based opinion summarization (HAOS) phase enriches this hierarchy with customers’ opinions to be shown to other potential buyers. To test the feasibility of using deep learning-based BERT techniques with our approach, we created a corpus by gathering information from the top five EC websites for laptops. The experimental results showed that recurrent neural network (RNN) achieved better results (77.4% and 82.6% in terms of F1-measure for the first and second phases, respectively) than the convolutional neural network (CNN) and the support vector machine (SVM) technique.

scholarly journals Read what you need: Controllable Aspect-based Opinion Summarization of Tourist Reviews

2020 ◽  
Author(s):  
Rajdeep Mukherjee ◽  
Hari Chandana Peruri ◽  
Uppada Vishnu ◽  
Pawan Goyal ◽  
Sourangshu Bhattacharya ◽  
...  
Keyword(s):  
Opinion Summarization
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