Search Results for author: Ikechukwu Onyenwe

Found 9 papers, 0 papers with code

Developing Smart Web-Search Using RegEx

no code implementations10 Oct 2021 Ikechukwu Onyenwe, Stanley Ogbonna, Ebele Onyedimma, Onyedikachukwu Ikechukwu-Onyenwe, Chidinma Nwafor

The idea is to embed regEx patterns as part of the search engine's algorithm in a web application project to provide strings related to the targeted items for more comprehensive coverage of search results.

Developing Products Update-Alert System for e-Commerce Websites Users Using HTML Data and Web Scraping Technique

no code implementations2 Sep 2021 Ikechukwu Onyenwe, Ebele Onyedinma, Chidinma Nwafor, Obinna Agbata

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.

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

no code implementations7 Jul 2020 Ikechukwu Onyenwe, Samuel Nwagbo, Njideka Mbeledogu, Ebele Onyedinma

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).

Sentiment Analysis

Igbo-English Machine Translation: An Evaluation Benchmark

no code implementations1 Apr 2020 Ignatius Ezeani, Paul Rayson, Ikechukwu Onyenwe, Chinedu Uchechukwu, Mark Hepple

Although researchers and practitioners are pushing the boundaries and enhancing the capacities of NLP tools and methods, works on African languages are lagging.

Machine Translation Part-Of-Speech Tagging +1

Igbo Diacritic Restoration using Embedding Models

no code implementations NAACL 2018 Ignatius Ezeani, Mark Hepple, Ikechukwu Onyenwe, Enemouh Chioma

In this work, we applied embedding models to the diacritic restoration task and compared their performances to those of n-gram models.

Machine Translation Word Embeddings

Lexical Disambiguation of Igbo using Diacritic Restoration

no code implementations WS 2017 Ignatius Ezeani, Mark Hepple, Ikechukwu Onyenwe

However, as a classification task, diacritic restoration is well suited for and will be more generalisable with machine learning.

General Classification

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