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- | title = An Automatic Method for Wordnet Concept Enrichment Using Wikipedia Titles '''An Automatic Method for Wordnet Concept Enrichment Using Wikipedia Titles''' - scientific work related to [2 KB (323 words) - 14:47, 3 December 2020
- ...d Youtube Video Categorization System from Meta Data & User Comments Using Wordnet & Wikipedia ...d Youtube Video Categorization System from Meta Data & User Comments Using Wordnet & Wikipedia''' - scientific work related to [[Wikipedia quality]] published3 KB (414 words) - 12:54, 24 March 2021
- | title = Tracking the Lexical Zeitgeist with Wordnet and Wikipedia '''Tracking the Lexical Zeitgeist with Wordnet and Wikipedia''' - scientific work related to [[Wikipedia quality]] publish2 KB (266 words) - 11:34, 14 June 2020
- | title = Aligning Wordnet Synsets and Wikipedia Articles '''Aligning Wordnet Synsets and Wikipedia Articles''' - scientific work related to [[Wikipedia2 KB (247 words) - 19:09, 17 October 2020
- | title = Mapping Wordnet Synsets to Wikipedia Articles '''Mapping Wordnet Synsets to Wikipedia Articles''' - scientific work related to [[Wikipedia q2 KB (241 words) - 08:28, 23 February 2021
- | title = Yago: a Core of Semantic Knowledgeunifying Wordnet and Wikipedia '''Yago: a Core of Semantic Knowledgeunifying Wordnet and Wikipedia''' - scientific work related to [[Wikipedia quality]] publish3 KB (329 words) - 03:55, 29 December 2020
- ...Web Meets Linguistic Knowledge: Automatic Sense Alignment of Wikipedia and Wordnet ...Web Meets Linguistic Knowledge: Automatic Sense Alignment of Wikipedia and Wordnet''' - scientific work related to [[Wikipedia quality]] published in 2011, wr2 KB (323 words) - 05:40, 29 January 2021
- | title = Comparing Wikipedia and German Wordnet by Evaluating Semantic Relatedness on Multiple Datasets '''Comparing Wikipedia and German Wordnet by Evaluating Semantic Relatedness on Multiple Datasets''' - scientific wor3 KB (316 words) - 10:22, 8 February 2021
Page text matches
- .... While tags usually associated with concepts in some databases, such as [[WordNet]] and online ontologies. However, these databases are stable, static and la2 KB (278 words) - 00:56, 20 May 2019
- ...n Wikipedia in five different languages and compare the results with the [[WordNet]] taxonomy and a [[multilingual]] approach based on interwiki links of the3 KB (400 words) - 23:42, 20 May 2019
- | title = Automatic Extraction of Semantic Relationships for Wordnet by Means of Pattern Learning from Wikipedia '''Automatic Extraction of Semantic Relationships for Wordnet by Means of Pattern Learning from Wikipedia''' - scientific work related to3 KB (328 words) - 22:15, 21 May 2019
- ...n of the extracted data as an additional knowledge source in automatic pl[[WordNet]] expansion.2 KB (302 words) - 08:08, 22 May 2019
- ...on Answering system based on the Inter Lingual Index (ILI) module of Euro[[WordNet]] is proposed and evaluated. This strategy overcomes the problems due to IL3 KB (377 words) - 08:46, 22 May 2019
- ...on of instances in Wikipedia and a well-structured top-level taxonomy from WordNet.2 KB (265 words) - 22:28, 22 May 2019
- ...pose. The best results on this dataset are obtained by integrating Google, WordNet and Wikipedia based measures. Authors also show that including Wikipedia im2 KB (257 words) - 22:56, 22 May 2019
- ...n a large scale resource. In contrast, this distinction has been made in [[WordNet]] and Cyc based on manual annotations. The result of the process is evaluat2 KB (293 words) - 10:19, 23 May 2019
- ...findings by transferring semantic [[relatedness]] algorithms defined on [[WordNet]] to the Wikipedia category graph. To assess the usefulness of the category2 KB (239 words) - 10:37, 23 May 2019
- ...ucture each event as a set of RDF triples linked to both [[DBpedia]] and [[WordNet]]. Authors point out examples of automatically mined events, providing some3 KB (398 words) - 12:07, 10 May 2020
- ...comparable way in Wikipedia. The concepts in 6 taxonomies extracted from [[WordNet]] are mapped onto Wikipedia pages and the lexico-syntactic patterns describ2 KB (222 words) - 07:12, 16 January 2021
- ...iques that enhance previously published approaches by employing both the [[WordNet]] lexical database and the Wikipedia article's PageRank scores in the disam3 KB (376 words) - 23:14, 16 July 2019
- | title = Yago: a Core of Semantic Knowledge Unifying Wordnet and Wikipedia '''Yago: a Core of Semantic Knowledge Unifying Wordnet and Wikipedia''' - scientific work related to [[Wikipedia quality]] publish3 KB (336 words) - 22:18, 2 October 2020
- ...dNet]]. However, many of these approaches suffer from some limitations: 1) WordNet has limited coverage and has a lack of effective word-sense disambiguation3 KB (422 words) - 01:04, 17 February 2021
- ...are exploited to extract instances for the sense of each ambiguous word in WordNet. For handling the lack of instances of some articles in Wikipedia, the mult3 KB (426 words) - 22:09, 14 July 2019
- ...f background knowledge, on limited lexicographic knowledge bases such as [[WordNet]], or on huge manual efforts such as the CYC project. Here authors propose3 KB (346 words) - 10:23, 4 April 2021
- ...sing the Learning of Lexical Patterns: an Application to the Enrichment of Wordnet by Extracting Semantic Relationships from Wikipedia ...sing the Learning of Lexical Patterns: an Application to the Enrichment of Wordnet by Extracting Semantic Relationships from Wikipedia''' - scientific work re3 KB (394 words) - 08:28, 16 January 2020
- ...f this research is the semi-automatic enrichment of senses from the German wordnet GermaNet with corpus examples from the online encyclopedia [[Wikipedia]]. T3 KB (384 words) - 09:22, 9 November 2019
- Taxonomy-Based Information Content and Wordnet-Wiktionary-Wikipedia Glosses for Semantic Relatedness| title = Taxonomy-Based Information Content and Wordnet-Wiktionary-Wikipedia Glosses for Semantic Relatedness '''Taxonomy-Based Information Content and Wordnet-Wiktionary-Wikipedia Glosses for Semantic Relatedness''' - scientific work4 KB (473 words) - 00:55, 12 February 2021
- | title = Minimally Supervised Question Classification and Answering based on Wordnet and Wikipedia '''Minimally Supervised Question Classification and Answering based on Wordnet and Wikipedia''' - scientific work related to [[Wikipedia quality]] publish2 KB (291 words) - 10:15, 4 September 2019