Title
Named Entity Recognition for Afan Oromo: Developing Named Entity Recognition for Resource Scarce Languages,Used
Sold by Ergodebooks, an authorized reseller.
Returns accepted within 30 days | support@ergodebooks.com
Shipping Information
- Free Standard Shipping — United States only
- Processing Time: 1–3 business days
- Estimated Delivery: 3–5 business days after dispatch
- Double-boxed, fully insured & discreetly packaged
- Tracking number sent via email once dispatched
- Orders over $250 require signature upon delivery. Taxes calculated at checkout.
Returns & Refund
Returns accepted within 30 days of delivery.
Damaged or Defective Item
Free return shipping + replacement or full refund
Wrong Item Received
Free return shipping + replacement or full refund
Change of Mind
Return shipping at customer's expense · 25% restocking fee applies
Named Entity Recognition (NER) is an information extraction task aimed at identifying and classifying words of a sentence, a paragraph or a document into predefined categories of Named Entities (NEs). NEs are terms that are used to name a person, location or organization. They are also used to refer to the value or amount of something. NER is an important tool in almost all NLP application areas out of which it is very essential in Search Engines (Semantic based), Machine Translation, QuestionAnswering, Indexing for Information Retrieval and Automatic Summarization systems. A lot of NER researches have been conducted and systems have been developed for a resource rich European and Asian languages. This book proposes and presents the development of NER system for Afan Oromo, a language that has the largest native speakers in Ethiopia. The algorithms and techniques presented in this study have shown good performance thereby reflecting how NER system can be developed for a resource scarce languages.
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.