Matches in SemOpenAlex for { <https://semopenalex.org/work/W4378472014> ?p ?o ?g. }
Showing items 1 to 58 of
58
with 100 items per page.
- W4378472014 endingPage "230" @default.
- W4378472014 startingPage "222" @default.
- W4378472014 abstract "Lexicons are a lexical resource that has been used successfully in sentiment analysis and other areas of natural language processing. Although there are several unweighted lexicons and weighted lexicons, they all achieve poor performance in many applications. This is because they are created in general contexts, and adding more terms to an existing lexicon is complicated. Furthermore, current methods for generating weighted lexicons are complex and not very intuitive. In this article, we show the results of a method to generate weighted lexicons from a tagged corpus. The terms that make up the lexicon, as well as the corresponding weights, are obtained by means of a distance measure that is closely related to the probability that a document belongs to its label. The preliminary results obtained with a corpus of 405 documents show that the method reaches an accuracy of 92.3%." @default.
- W4378472014 created "2023-05-27" @default.
- W4378472014 creator A5036736059 @default.
- W4378472014 creator A5065258336 @default.
- W4378472014 creator A5088159892 @default.
- W4378472014 creator A5092030636 @default.
- W4378472014 date "2023-01-01" @default.
- W4378472014 modified "2023-09-26" @default.
- W4378472014 title "Retrieval of Weighted Lexicons Based on Supervised Learning Method" @default.
- W4378472014 cites W2081580037 @default.
- W4378472014 cites W2099813784 @default.
- W4378472014 cites W2160660844 @default.
- W4378472014 cites W3094173182 @default.
- W4378472014 cites W3124019418 @default.
- W4378472014 cites W3171798841 @default.
- W4378472014 doi "https://doi.org/10.1007/978-3-031-34222-6_19" @default.
- W4378472014 hasPublicationYear "2023" @default.
- W4378472014 type Work @default.
- W4378472014 citedByCount "0" @default.
- W4378472014 crossrefType "book-chapter" @default.
- W4378472014 hasAuthorship W4378472014A5036736059 @default.
- W4378472014 hasAuthorship W4378472014A5065258336 @default.
- W4378472014 hasAuthorship W4378472014A5088159892 @default.
- W4378472014 hasAuthorship W4378472014A5092030636 @default.
- W4378472014 hasConcept C124101348 @default.
- W4378472014 hasConcept C154945302 @default.
- W4378472014 hasConcept C204321447 @default.
- W4378472014 hasConcept C23123220 @default.
- W4378472014 hasConcept C2778121359 @default.
- W4378472014 hasConcept C2780009758 @default.
- W4378472014 hasConcept C41008148 @default.
- W4378472014 hasConcept C66402592 @default.
- W4378472014 hasConceptScore W4378472014C124101348 @default.
- W4378472014 hasConceptScore W4378472014C154945302 @default.
- W4378472014 hasConceptScore W4378472014C204321447 @default.
- W4378472014 hasConceptScore W4378472014C23123220 @default.
- W4378472014 hasConceptScore W4378472014C2778121359 @default.
- W4378472014 hasConceptScore W4378472014C2780009758 @default.
- W4378472014 hasConceptScore W4378472014C41008148 @default.
- W4378472014 hasConceptScore W4378472014C66402592 @default.
- W4378472014 hasLocation W43784720141 @default.
- W4378472014 hasOpenAccess W4378472014 @default.
- W4378472014 hasPrimaryLocation W43784720141 @default.
- W4378472014 hasRelatedWork W1484312846 @default.
- W4378472014 hasRelatedWork W1994972134 @default.
- W4378472014 hasRelatedWork W2467206427 @default.
- W4378472014 hasRelatedWork W2626568907 @default.
- W4378472014 hasRelatedWork W2965885965 @default.
- W4378472014 hasRelatedWork W3011677438 @default.
- W4378472014 hasRelatedWork W3153487575 @default.
- W4378472014 hasRelatedWork W4200526184 @default.
- W4378472014 hasRelatedWork W4226173368 @default.
- W4378472014 hasRelatedWork W3205826705 @default.
- W4378472014 isParatext "false" @default.
- W4378472014 isRetracted "false" @default.
- W4378472014 workType "book-chapter" @default.