Ebele Onyedinma

CV
h-index3
3papers
14citations
Novelty10%
AI Score12

3 Papers

3.6IRSep 2, 2021
Developing Products Update-Alert System for e-Commerce Websites Users Using HTML Data and Web Scraping Technique

Ikechukwu Onyenwe, Ebele Onyedinma, Chidinma Nwafor et al.

Websites are regarded as domains of limitless information which anyone and everyone can access. The new trend of technology put us to change the way we are doing our business. The Internet now is fastly becoming a new place for business and the advancement in this technology gave rise to the number of e-commerce websites. This made the lifestyle of marketers/vendors, retailers and consumers (collectively regarded as users in this paper) easy, because it provides easy platforms to sale/order items through the internet. This also requires that the users will have to spend a lot of time and effort to search for the best product deals, products updates and offers on e-commerce websites. They have to filter and compare search results by themselves which takes a lot of time and there are chances of ambiguous results. In this paper, we applied web crawling and scraping methods on an e-commerce website to get HTML data for identifying products updates based on the current time. The HTML data is preprocessed to extract details of the products such as name, price, post date and time, etc. to serve as useful information for users.

2.3SIJul 7, 2020
The impact of political party/candidate on the election results from a sentiment analysis perspective using #AnambraDecides2017 tweets

Ikechukwu Onyenwe, Samuel Nwagbo, Njideka Mbeledogu et al.

This work investigates empirically the impact of political party control over its candidates or vice versa on winning an election using a natural language processing technique called sentiment analysis (SA). To do this, a set of 7430 tweets bearing or related to #AnambraDecides2017 was streamed during the November 18, 2017, Anambra State gubernatorial election. These are Twitter discussions on the top five political parties and their candidates termed political actors in this paper. We conduct polarity and subjectivity sentiment analyses on all the tweets considering time as a useful dimension of SA. Furthermore, we use the word frequency to find words most associated with the political actors in a given time. We find most talked about topics using a topic modeling algorithm and how the computed sentiments and most frequent words are related to the topics per political actor. Among other things, we deduced from the experimental results that even though a political party serves as a platform that sales the personality of a candidate, the acceptance of the candidate/party adds to the winning of an election. For example, we found the winner of the election Willie Obiano benefiting from the values his party share among the people of the State. Associating his name with his party, All Progressive Grand Alliance (APGA) displays more positive sentiments and the subjective sentiment analysis indicates that Twitter users mentioning APGA are less emotionally subjective in their tweets than the other parties.

0.9CVSep 1, 2019
Performance Evaluation of Histogram Equalization and Fuzzy image Enhancement Techniques on Low Contrast Images

E Onyedinma, I Onyenwe, H Inyiama

Image enhancement aims at improving the information content of original image for a specific purpose. This purpose could be for visual interpretation or for effective extraction of required details. Nevertheless, some acquired images are often associated with pixels of low dynamic range and as such result in low contrast images. Enhancing the contrast therefore tends to increase the dynamic range of the gray levels in the acquired image so as to span the full intensity range. Techniques such as Histogram Equalization (HE) and fuzzy technique can be adopted for contrast enhancement. HE adjusts the contrast of an input image by modifying the intensity distribution of its histogram. It is characterized by providing a global approach to image enhancement, computationally fast and easy to implement approach but can introduce unnatural artifacts and other undesirable elements to the resulting image. Fuzzy technique on its part enhances image by mapping the image gray level intensities into a fuzzy plane using membership functions; modifying the membership functions as desired and mapping back into the gray level plane. Thus, details at desired areas can be enhanced at the expense of increase in computational cost. This paper explores the effect of the use of HE and fuzzy technique to enhance low contrast images. Their performances are evaluated using the Mean squared error (MSE), Peak to signal noise ratio (PSNR), entropy and Absolute mean brightness error (AMBE).