Difference between revisions of "Semantic Tag Recommendation based on Associated Words Exploiting the Interwiki Links of Wikipedia"
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== Overview == | == Overview == | ||
The volumes of multimedia content and users have increased on social multimedia sites due to the prevalence of smart mobile devices and digital cameras. It is common for users to take pictures and upload them to image-sharing websites using their smartphones. However, the tag characteristics deteriorate the quality of tag-based image retrieval and decrease the [[reliability]] of social multimedia sites. In this article, authors propose a semantic tag recommendation technique exploiting associated words that are semantically similar or related to each other using the interwiki links of [[Wikipedia]]. First, authors generate a word relationship graph after extracting meaningful words from each article in Wikipedia. The candidate words are then rearranged according to importance by applying a link-based ranking algorithm and then the top-k words are defined as the associated words for the article. When a user uploads an image, authors collect visually similar images from a social image database. After propagating the proper tags f... | The volumes of multimedia content and users have increased on social multimedia sites due to the prevalence of smart mobile devices and digital cameras. It is common for users to take pictures and upload them to image-sharing websites using their smartphones. However, the tag characteristics deteriorate the quality of tag-based image retrieval and decrease the [[reliability]] of social multimedia sites. In this article, authors propose a semantic tag recommendation technique exploiting associated words that are semantically similar or related to each other using the interwiki links of [[Wikipedia]]. First, authors generate a word relationship graph after extracting meaningful words from each article in Wikipedia. The candidate words are then rearranged according to importance by applying a link-based ranking algorithm and then the top-k words are defined as the associated words for the article. When a user uploads an image, authors collect visually similar images from a social image database. After propagating the proper tags f... | ||
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| + | == Embed == | ||
| + | === Wikipedia Quality === | ||
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| + | <nowiki> | ||
| + | Hong, Hyun-Ki; Kim, Gun-Woo; Lee, Dong-Ho. (2018). "[[Semantic Tag Recommendation based on Associated Words Exploiting the Interwiki Links of Wikipedia]]". SAGE PublicationsSage UK: London, England. DOI: 10.1177/0165551517693497. | ||
| + | </nowiki> | ||
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| + | === English Wikipedia === | ||
| + | <code> | ||
| + | <nowiki> | ||
| + | {{cite journal |last1=Hong |first1=Hyun-Ki |last2=Kim |first2=Gun-Woo |last3=Lee |first3=Dong-Ho |title=Semantic Tag Recommendation based on Associated Words Exploiting the Interwiki Links of Wikipedia |date=2018 |doi=10.1177/0165551517693497 |url=https://wikipediaquality.com/wiki/Semantic_Tag_Recommendation_based_on_Associated_Words_Exploiting_the_Interwiki_Links_of_Wikipedia |journal=SAGE PublicationsSage UK: London, England}} | ||
| + | </nowiki> | ||
| + | </code> | ||
| + | |||
| + | === HTML === | ||
| + | <code> | ||
| + | <nowiki> | ||
| + | Hong, Hyun-Ki; Kim, Gun-Woo; Lee, Dong-Ho. (2018). &quot;<a href="https://wikipediaquality.com/wiki/Semantic_Tag_Recommendation_based_on_Associated_Words_Exploiting_the_Interwiki_Links_of_Wikipedia">Semantic Tag Recommendation based on Associated Words Exploiting the Interwiki Links of Wikipedia</a>&quot;. SAGE PublicationsSage UK: London, England. DOI: 10.1177/0165551517693497. | ||
| + | </nowiki> | ||
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Revision as of 06:50, 13 June 2020
Authors | Hyun-Ki Hong Gun-Woo Kim Dong-Ho Lee |
|---|---|
Publication date | 2018 |
DOI | 10.1177/0165551517693497 |
Links | Original |
Semantic Tag Recommendation based on Associated Words Exploiting the Interwiki Links of Wikipedia - scientific work related to Wikipedia quality published in 2018, written by Hyun-Ki Hong, Gun-Woo Kim and Dong-Ho Lee.
Overview
The volumes of multimedia content and users have increased on social multimedia sites due to the prevalence of smart mobile devices and digital cameras. It is common for users to take pictures and upload them to image-sharing websites using their smartphones. However, the tag characteristics deteriorate the quality of tag-based image retrieval and decrease the reliability of social multimedia sites. In this article, authors propose a semantic tag recommendation technique exploiting associated words that are semantically similar or related to each other using the interwiki links of Wikipedia. First, authors generate a word relationship graph after extracting meaningful words from each article in Wikipedia. The candidate words are then rearranged according to importance by applying a link-based ranking algorithm and then the top-k words are defined as the associated words for the article. When a user uploads an image, authors collect visually similar images from a social image database. After propagating the proper tags f...
Embed
Wikipedia Quality
Hong, Hyun-Ki; Kim, Gun-Woo; Lee, Dong-Ho. (2018). "[[Semantic Tag Recommendation based on Associated Words Exploiting the Interwiki Links of Wikipedia]]". SAGE PublicationsSage UK: London, England. DOI: 10.1177/0165551517693497.
English Wikipedia
{{cite journal |last1=Hong |first1=Hyun-Ki |last2=Kim |first2=Gun-Woo |last3=Lee |first3=Dong-Ho |title=Semantic Tag Recommendation based on Associated Words Exploiting the Interwiki Links of Wikipedia |date=2018 |doi=10.1177/0165551517693497 |url=https://wikipediaquality.com/wiki/Semantic_Tag_Recommendation_based_on_Associated_Words_Exploiting_the_Interwiki_Links_of_Wikipedia |journal=SAGE PublicationsSage UK: London, England}}
HTML
Hong, Hyun-Ki; Kim, Gun-Woo; Lee, Dong-Ho. (2018). "<a href="https://wikipediaquality.com/wiki/Semantic_Tag_Recommendation_based_on_Associated_Words_Exploiting_the_Interwiki_Links_of_Wikipedia">Semantic Tag Recommendation based on Associated Words Exploiting the Interwiki Links of Wikipedia</a>". SAGE PublicationsSage UK: London, England. DOI: 10.1177/0165551517693497.
