Matches in SemOpenAlex for { <https://semopenalex.org/work/W2561209063> ?p ?o ?g. }
Showing items 1 to 79 of
79
with 100 items per page.
- W2561209063 endingPage "506" @default.
- W2561209063 startingPage "496" @default.
- W2561209063 abstract "Image is one of the most important means to express users' emotions on microblogging, like Sina Weibo. More and more people post only images on it, due to the fast and convenient nature of image. Taking a post only using images on microblogging has been a new tendency. Most existing studies about sentiment analysis on microblogging focus on the text, or integrate image as an auxiliary information into text, so they are not applicable in this scenario. Although a few methods related to sentiment analysis for image have been proposed, most of them either ignore the semantic gap between low-level visual features and higher-level image sentiments, or require a lot of textual information in the phases of both training and inference. This paper proposes a new sentiment analysis method based on Simple Multiple Kernel Learning (SimpleMKL). Specifically, textual information as a sort of sufficiently emotional source data, we can use it to promote the ability via SimpleMKL to classify images. And once we get the image classifier, none of texts are needed when predicting other unlabelled images. Experimental results show that our proposed method can improve the performance significantly on data we crawled and labelled from Sina Weibo. We find that our method not only outperforms some common methods, like SVM, Naive Bayes, KNN, Random Forest, Adaboost, etc., using the image features of colour, hog, texture, but also outperforms some state-of-the-art methods." @default.
- W2561209063 created "2017-01-06" @default.
- W2561209063 creator A5032500191 @default.
- W2561209063 creator A5042942092 @default.
- W2561209063 creator A5063402368 @default.
- W2561209063 creator A5072069474 @default.
- W2561209063 date "2016-01-01" @default.
- W2561209063 modified "2023-09-26" @default.
- W2561209063 title "Sentiment Analysis for Images on Microblogging by Integrating Textual Information with Multiple Kernel Learning" @default.
- W2561209063 cites W1484353406 @default.
- W2561209063 cites W1714665356 @default.
- W2561209063 cites W1988445395 @default.
- W2561209063 cites W2001700175 @default.
- W2561209063 cites W2020438140 @default.
- W2561209063 cites W2075456404 @default.
- W2561209063 cites W2082398333 @default.
- W2561209063 cites W2110700950 @default.
- W2561209063 cites W2113319895 @default.
- W2561209063 cites W2114524997 @default.
- W2561209063 cites W2273818082 @default.
- W2561209063 cites W2397331935 @default.
- W2561209063 cites W4205184193 @default.
- W2561209063 cites W4211186029 @default.
- W2561209063 cites W4243801427 @default.
- W2561209063 doi "https://doi.org/10.1007/978-3-319-42911-3_41" @default.
- W2561209063 hasPublicationYear "2016" @default.
- W2561209063 type Work @default.
- W2561209063 sameAs 2561209063 @default.
- W2561209063 citedByCount "5" @default.
- W2561209063 countsByYear W25612090632017 @default.
- W2561209063 countsByYear W25612090632018 @default.
- W2561209063 countsByYear W25612090632020 @default.
- W2561209063 countsByYear W25612090632021 @default.
- W2561209063 crossrefType "book-chapter" @default.
- W2561209063 hasAuthorship W2561209063A5032500191 @default.
- W2561209063 hasAuthorship W2561209063A5042942092 @default.
- W2561209063 hasAuthorship W2561209063A5063402368 @default.
- W2561209063 hasAuthorship W2561209063A5072069474 @default.
- W2561209063 hasConcept C114614502 @default.
- W2561209063 hasConcept C136764020 @default.
- W2561209063 hasConcept C143275388 @default.
- W2561209063 hasConcept C154945302 @default.
- W2561209063 hasConcept C204321447 @default.
- W2561209063 hasConcept C23123220 @default.
- W2561209063 hasConcept C33923547 @default.
- W2561209063 hasConcept C41008148 @default.
- W2561209063 hasConcept C518677369 @default.
- W2561209063 hasConcept C66402592 @default.
- W2561209063 hasConcept C74193536 @default.
- W2561209063 hasConceptScore W2561209063C114614502 @default.
- W2561209063 hasConceptScore W2561209063C136764020 @default.
- W2561209063 hasConceptScore W2561209063C143275388 @default.
- W2561209063 hasConceptScore W2561209063C154945302 @default.
- W2561209063 hasConceptScore W2561209063C204321447 @default.
- W2561209063 hasConceptScore W2561209063C23123220 @default.
- W2561209063 hasConceptScore W2561209063C33923547 @default.
- W2561209063 hasConceptScore W2561209063C41008148 @default.
- W2561209063 hasConceptScore W2561209063C518677369 @default.
- W2561209063 hasConceptScore W2561209063C66402592 @default.
- W2561209063 hasConceptScore W2561209063C74193536 @default.
- W2561209063 hasLocation W25612090631 @default.
- W2561209063 hasOpenAccess W2561209063 @default.
- W2561209063 hasPrimaryLocation W25612090631 @default.
- W2561209063 hasRelatedWork W1983021219 @default.
- W2561209063 hasRelatedWork W2088249598 @default.
- W2561209063 hasRelatedWork W2107474859 @default.
- W2561209063 hasRelatedWork W2380640591 @default.
- W2561209063 hasRelatedWork W2752287943 @default.
- W2561209063 hasRelatedWork W2790130690 @default.
- W2561209063 hasRelatedWork W2899665927 @default.
- W2561209063 hasRelatedWork W2970654292 @default.
- W2561209063 hasRelatedWork W3115590054 @default.
- W2561209063 hasRelatedWork W40549020 @default.
- W2561209063 isParatext "false" @default.
- W2561209063 isRetracted "false" @default.
- W2561209063 magId "2561209063" @default.
- W2561209063 workType "book-chapter" @default.