Matches in SemOpenAlex for { <https://semopenalex.org/work/W2016459931> ?p ?o ?g. }
Showing items 1 to 53 of
53
with 100 items per page.
- W2016459931 abstract "Twitter has evolved into a powerful communication and information sharing tool used by millions of people around the world to post what is happening now. A hashtag, a keyword prefixed with a hash symbol (#), is a feature in Twitter to organize tweets and facilitate effective search among a massive volume of data. In this paper, we propose an automatic hashtag recommendation system that helps users find new hashtags related to their interests. We propose the Hashtag Frequency-Inverse Hashtag Ubiquity (HF-IHU) ranking scheme, which is a variation of the well-known TF-IDF, that considers hashtag relevancy, as well as data sparseness. Experiments on a large Twitter data set demonstrate that our method successfully yields relevant hashtags for user's interest and that recommendations more stable and reliable than ranking tags based on tweet content similarity. Our results show that HF-IHU can achieve over 30% hashtag recall when asked to identify the top 10 relevant hashtags for a particular tweet." @default.
- W2016459931 created "2016-06-24" @default.
- W2016459931 creator A5018161805 @default.
- W2016459931 creator A5018697304 @default.
- W2016459931 creator A5067685166 @default.
- W2016459931 date "2014-01-01" @default.
- W2016459931 modified "2023-09-22" @default.
- W2016459931 title "Design and evaluation of a Twitter hashtag recommendation system" @default.
- W2016459931 cites W1521626219 @default.
- W2016459931 cites W1553232534 @default.
- W2016459931 cites W1683269307 @default.
- W2016459931 cites W1996235486 @default.
- W2016459931 cites W2013994393 @default.
- W2016459931 cites W2027323723 @default.
- W2016459931 cites W2053968437 @default.
- W2016459931 cites W2144211451 @default.
- W2016459931 cites W72664156 @default.
- W2016459931 doi "https://doi.org/10.1145/2628194.2628238" @default.
- W2016459931 hasPublicationYear "2014" @default.
- W2016459931 type Work @default.
- W2016459931 sameAs 2016459931 @default.
- W2016459931 citedByCount "24" @default.
- W2016459931 countsByYear W20164599312015 @default.
- W2016459931 countsByYear W20164599312016 @default.
- W2016459931 countsByYear W20164599312017 @default.
- W2016459931 countsByYear W20164599312018 @default.
- W2016459931 countsByYear W20164599312019 @default.
- W2016459931 countsByYear W20164599312020 @default.
- W2016459931 countsByYear W20164599312021 @default.
- W2016459931 countsByYear W20164599312022 @default.
- W2016459931 crossrefType "proceedings-article" @default.
- W2016459931 hasAuthorship W2016459931A5018161805 @default.
- W2016459931 hasAuthorship W2016459931A5018697304 @default.
- W2016459931 hasAuthorship W2016459931A5067685166 @default.
- W2016459931 hasConcept C41008148 @default.
- W2016459931 hasConceptScore W2016459931C41008148 @default.
- W2016459931 hasLocation W20164599311 @default.
- W2016459931 hasOpenAccess W2016459931 @default.
- W2016459931 hasPrimaryLocation W20164599311 @default.
- W2016459931 hasRelatedWork W2093578348 @default.
- W2016459931 hasRelatedWork W2096946506 @default.
- W2016459931 hasRelatedWork W2350741829 @default.
- W2016459931 hasRelatedWork W2358668433 @default.
- W2016459931 hasRelatedWork W2376932109 @default.
- W2016459931 hasRelatedWork W2382290278 @default.
- W2016459931 hasRelatedWork W2390279801 @default.
- W2016459931 hasRelatedWork W2748952813 @default.
- W2016459931 hasRelatedWork W2766271392 @default.
- W2016459931 hasRelatedWork W2899084033 @default.
- W2016459931 isParatext "false" @default.
- W2016459931 isRetracted "false" @default.
- W2016459931 magId "2016459931" @default.
- W2016459931 workType "article" @default.