This Natural Language Processing question bank is designed for BS Computing students following the NCEAC syllabus. Here you will find 100 MCQs, 30 short questions and 15 long / theory questions covering all topics from Lectures 1–15, including text preprocessing,…
Extractive and abstractive text summarization techniques with examples and evaluation metrics like ROUGE. As the volume of digital text continues to grow, it is no longer practical for humans to read every article, report or judgment in full. Text summarization…
How question answering systems work, from information retrieval based pipelines to modern neural approaches in Natural Language Processing. Question answering systems aim to respond to natural language questions with precise answers rather than long lists of documents. Instead of simply…
How machine translation evolved from rule based and statistical methods to modern neural MT with attention. Automatic translation of human languages is one of the oldest and most ambitious goals in Natural Language Processing. Decades before deep learning, researchers tried…
Explore information extraction, named entity recognition and relation extraction using dependency and constituency grammars. Most text on the web is unstructured. Articles, news, emails and social media posts are easy for humans to read but difficult for machines to query…
Understand information retrieval basics, vector space model, cosine similarity and evaluation using precision and recall. Search is one of the most visible applications of Natural Language Processing. Whenever a user types “best deep learning tutorials”, “POS tagging example in Python”…