Named entity recognition (NER) is a natural language processing (NLP) problem that is mainly used for text summarization, data mining, data retrieval, question and answering, machine translation, and document classification systems. A NER system is tasked with determining the border of each named entity, recognizing its type and classifying it into predefined categories. The categories of named...

One of the most primary phases of automatic text processing is spelling error detection and grapheme normalization. Storing textual documents faces several problems without passing this phase, which causes a disturbance in retrieving the documents automatically. Therefore, specialists in the fields of natural language processing and computational linguistics usually make an attempt to sample va...

A significant amount of available information is stored in textual databases which contains a large collection of documents from different sources (such as news, articles, books, emails and web pages). The increasing visibility and importance of this class of information motivates us to work on having better automatic evaluation tools for textual resources. The automatic summarization of tex...