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keyword extraction (keywords are chosen from words that are explicitly mentioned in original text). Methods for automatic keyword extraction can be supervised, semi-supervised, or unsupervised. [ 4 ] Unsupervised methods can be further divided into simple statistics, linguistics or graph-based, or ensemble methods that combine some or most of ...
Terminology extraction (also known as term extraction, glossary extraction, term recognition, or terminology mining) is a subtask of information extraction.The goal of terminology extraction is to automatically extract relevant terms from a given corpus.
Sentence extraction is a technique used for automatic summarization of a text. In this shallow approach, statistical heuristics are used to identify the most salient sentences of a text. Sentence extraction is a low-cost approach compared to more knowledge-intensive deeper approaches which require additional knowledge bases such as ontologies ...
At the terminology extraction level, lexical terms from the text are extracted. For this purpose a tokenizer determines at first the word boundaries and solves abbreviations. Afterwards terms from the text, which correspond to a concept, are extracted with the help of a domain-specific lexicon to link these at entity linking.
Recent effort on adaptive information extraction motivates the development of IE systems that can handle different types of text, from well-structured to almost free text -where common wrappers fail- including mixed types. Such systems can exploit shallow natural language knowledge and thus can be also applied to less structured texts.
The method, also called latent semantic analysis (LSA), uncovers the underlying latent semantic structure in the usage of words in a body of text and how it can be used to extract the meaning of the text in response to user queries, commonly referred to as concept searches.
The indexer must then identify terms which appropriately identify the subject either by extracting words directly from the document or assigning words from a controlled vocabulary. [1] The terms in the index are then presented in a systematic order. Indexers must decide how many terms to include and how specific the terms should be.
In text retrieval, full-text search refers to techniques for searching a single computer-stored document or a collection in a full-text database.Full-text search is distinguished from searches based on metadata or on parts of the original texts represented in databases (such as titles, abstracts, selected sections, or bibliographical references).