scholarly journals Evaluating an Aspect Extraction Method for Opinion Mining in the Portuguese Language

2020 ◽  
Author(s):  
Breno Cardoso ◽  
Denilson Pereira
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Extraction Method ◽  
English Language ◽  
Opinion Mining ◽  
Aspect Extraction ◽  
Automatic Interpretation ◽  
Other Consumers

The opinion issued by consumers of products and services has become increasingly valued, both by other consumers and by companies. The automatic interpretation of review texts to generate information is of paramount importance. With opinion mining at the aspect level, it is possible to extract and summarize opinions about different components of a product or service. This paper evaluates the behavior of a method for extracting aspects using natural language processing tools for the Portuguese language. The aim is to investigate the maturity of the tools for Portuguese compared to the already consolidated tools for the English language. The evaluation was carried out in three datasets from two different domains with original texts in Portuguese and their translations into English, and vice versa, and the results indicate that there is no difference between languages.

Design of GA and Ontology based NLP Frameworks for Online Opinion Mining

2019 ◽  
Vol 13 (2) ◽  
pp. 159-165
Author(s):  
Manik Sharma ◽  
Gurvinder Singh ◽  
Rajinder Singh
Keyword(s):  
Genetic Algorithm ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Opinion Mining ◽  
Hybrid Genetic Algorithm ◽  
Online Reviews ◽  
Middle Tier ◽  
Complete Set ◽  
Mining Model

Background: For almost every domain, a tremendous degree of data is accessible in an online and offline mode. Billions of users are daily posting their views or opinions by using different online applications like WhatsApp, Facebook, Twitter, Blogs, Instagram etc. Objective: These reviews are constructive for the progress of the venture, civilization, state and even nation. However, this momentous amount of information is useful only if it is collectively and effectively mined. Methodology: Opinion mining is used to extract the thoughts, expression, emotions, critics, appraisal from the data posted by different persons. It is one of the prevailing research techniques that coalesce and employ the features from natural language processing. Here, an amalgamated approach has been employed to mine online reviews. Results: To improve the results of genetic algorithm based opining mining patent, here, a hybrid genetic algorithm and ontology based 3-tier natural language processing framework named GAO_NLP_OM has been designed. First tier is used for preprocessing and corrosion of the sentences. Middle tier is composed of genetic algorithm based searching module, ontology for English sentences, base words for the review, complete set of English words with item and their features. Genetic algorithm is used to expedite the polarity mining process. The last tier is liable for semantic, discourse and feature summarization. Furthermore, the use of ontology assists in progressing more accurate opinion mining model. Conclusion: GAO_NLP_OM is supposed to improve the performance of genetic algorithm based opinion mining patent. The amalgamation of genetic algorithm, ontology and natural language processing seems to produce fast and more precise results. The proposed framework is able to mine simple as well as compound sentences. However, affirmative preceded interrogative, hidden feature and mixed language sentences still be a challenge for the proposed framework.

scholarly journals Keyword extraction method for machine reading comprehension based on natural language processing

2021 ◽  
Vol 1955 (1) ◽  
pp. 012072
Author(s):  
Ruiheng Li ◽  
Xuan Zhang ◽  
Chengdong Li ◽  
Zhongju Zheng ◽  
Zihang Zhou ◽  
...  
Keyword(s):  
Reading Comprehension ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Extraction Method ◽  
Keyword Extraction ◽  
Machine Reading

A Hindi Image Caption Generation Framework Using Deep Learning

2021 ◽  
Vol 20 (2) ◽  
pp. 1-19
Author(s):  
Santosh Kumar Mishra ◽  
Rijul Dhir ◽  
Sriparna Saha ◽  
Pushpak Bhattacharyya
Keyword(s):  
Computer Vision ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
English Language ◽  
Image Captioning ◽  
Textual Description ◽  
Proposed Model ◽  
Hindi Language ◽  
The Given

Image captioning is the process of generating a textual description of an image that aims to describe the salient parts of the given image. It is an important problem, as it involves computer vision and natural language processing, where computer vision is used for understanding images, and natural language processing is used for language modeling. A lot of works have been done for image captioning for the English language. In this article, we have developed a model for image captioning in the Hindi language. Hindi is the official language of India, and it is the fourth most spoken language in the world, spoken in India and South Asia. To the best of our knowledge, this is the first attempt to generate image captions in the Hindi language. A dataset is manually created by translating well known MSCOCO dataset from English to Hindi. Finally, different types of attention-based architectures are developed for image captioning in the Hindi language. These attention mechanisms are new for the Hindi language, as those have never been used for the Hindi language. The obtained results of the proposed model are compared with several baselines in terms of BLEU scores, and the results show that our model performs better than others. Manual evaluation of the obtained captions in terms of adequacy and fluency also reveals the effectiveness of our proposed approach. Availability of resources : The codes of the article are available at https://github.com/santosh1821cs03/Image_Captioning_Hindi_Language ; The dataset will be made available: http://www.iitp.ac.in/∼ai-nlp-ml/resources.html .

A Framework for the Generation of Class Diagram from Text Requirements using Natural language Processing

2021 ◽  
Vol 10 (1) ◽  
pp. 25-31
Keyword(s):  
Natural Language Processing ◽  
Software Development ◽  
Natural Language ◽  
Language Processing ◽  
English Language ◽  
Software Requirements ◽  
Class Diagram ◽  
Requirement Analysis ◽  
Part Of Speech ◽  
Software Engineers

The software development procedure begins with identifying the requirement analysis. The process levels of the requirements start from analysing the requirements to sketch the design of the program, which is very critical work for programmers and software engineers. Moreover, many errors will happen during the requirement analysis cycle transferring to other stages, which leads to the high cost of the process more than the initial specified process. The reason behind this is because of the specifications of software requirements created in the natural language. To minimize these errors, we can transfer the software requirements to the computerized form by the UML diagram. To overcome this, a device has been designed, which plans can provide semi-automatized aid for designers to provide UML class version from software program specifications using natural Language Processing techniques. The proposed technique outlines the class diagram in a well-known configuration and additionally facts out the relationship between instructions. In this research, we propose to enhance the procedure of producing the UML diagrams by utilizing the Natural Language, which will help the software development to analyze the software requirements with fewer errors and efficient way. The proposed approach will use the parser analyze and Part of Speech (POS) tagger to analyze the user requirements entered by the user in the English language. Then, extract the verbs and phrases, etc. in the user text. The obtained results showed that the proposed method got better results in comparison with other methods published in the literature. The proposed method gave a better analysis of the given requirements and better diagrams presentation, which can help the software engineers. Key words: Part of Speech,UM

scholarly journals Natural Language to SQL query Generation

2021 ◽  
Vol 9 (VI) ◽  
pp. 5069-5072
Author(s):  
Kiran Raj R
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
English Language ◽  
Regular Expression ◽  
Parts Of Speech ◽  
Query Generation ◽  
Sql Query ◽  
Speech Tagging ◽  
The Web

Today, everyone has a personal device to access the web. Every user tries to access the knowledge that they require through internet. Most of the knowledge is within the sort of a database. A user with limited knowledge of database will have difficulty in accessing the data in the database. Hence, there’s a requirement for a system that permits the users to access the knowledge within the database. The proposed method is to develop a system where the input be a natural language and receive an SQL query which is used to access the database and retrieve the information with ease. Tokenization, parts-of-speech tagging, lemmatization, parsing and mapping are the steps involved in the process. The project proposed would give a view of using of Natural Language Processing (NLP) and mapping the query in accordance with regular expression in English language to SQL.

Opinion Mining for Instructor Evaluations at the Autonomous University of Ciudad Juarez

2021 ◽  
pp. 427-444
Author(s):  
Rafael Jiménez ◽  
Vicente García ◽  
Abraham López ◽  
Alejandra Mendoza Carreón ◽  
Alan Ponce
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Opinion Mining ◽  
Experimental Results ◽  
Ciudad Juarez ◽  
Teaching Process ◽  
Instructor Evaluation ◽  
Negative Comments ◽  
Processing Techniques

The Autonomous University of Ciudad Juárez performs an instructor evaluation each semester to find strengths, weaknesses, and areas of opportunity during the teaching process. In this chapter, the authors show how opinion mining can be useful for labeling student comments as positives and negatives. For this purpose, a database was created using real opinions obtained from five professors of the UACJ over the last four years, covering a total of 20 subjects. Natural language processing techniques were used on the database to normalize its data. Experimental results using 1-NN and Bagging classifiers shows that it is possible to automatically label positive and negative comments with an accuracy of 80.13%.

scholarly journals Sentiment Analysis of Review Data of a Product Using Python

2018 ◽  
Vol 7 (3.12) ◽  
pp. 674
Author(s):  
P Santhi Priya ◽  
T Venkateswara Rao
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Sentiment Analysis ◽  
Language Processing ◽  
Opinion Mining ◽  
The Other ◽  
Product Reviews ◽  
Prime Problem

The other name of sentiment analysis is the opinion mining. It’s one of the primary objectives in a Natural Language Processing(NLP). Opinion mining is having a lot of audience lately. In our research we have taken up a prime problem of opinion mining which is theSentiment Polarity Categorization(SPC) that is very influential. We proposed a methodology for the SPC with explanations to the minute level. Apart from theories computations are made on both review standard and sentence standard categorization with benefitting outcomes. Also, the data that is represented here is from the product reviews given on the shopping site called Amazon.  

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