會議論文
| 學年 | 109 |
|---|---|
| 學期 | 2 |
| 發表日期 | 2021-04-23 |
| 作品名稱 | A Deep Learning Approach to Extract Integrated Meaningful Keywords from Social Network Posts with Images, Texts and Hashtags |
| 作品名稱（其他語言） | |
| 著者 | Ren-Xiang Lin; Chien-Chih Yu; Heng-Li Yang |
| 作品所屬單位 | |
| 出版者 | |
| 會議名稱 | 2021 ICT with Intelligent Applications |
| 會議地點 | Ahmedabad, India |
| 摘要 | Using the social network services, users might create different types of content including numeric, textual and non-textual data objects. In the past, social network service providers mainly focus on numeric and textual content to understand their users and to provide them with related information or advertisements. However, the information behind the non-textual content has not been well considered. This research aims at extracting integrated meaningful keywords by jointly considering photo, text descriptions and hashtags to better reflect the meaning of the user-posted content. A deep learning approach with convolutional neural network methods that integrate ResNet-50 and Word2Vec models, as well as Dijkstra’s algorithm is proposed to extract the meaningful keywords. The well-trained ResNet-50 and Word2Vec models are applied respectively to gain the predicted classification labels of the image and to identify the co-occurrences among predicted classification labels of image, segmented words of text descriptions and hashtags. A multistage graph weighted with the pairs of co-occurrences of image, segmented words and hashtags is built and then, the Dijkstra’s algorithm is adapted to extract consistent keywords of the posted content with maximized cumulated weights. A simplified example is provided to illustrate the proposed approach for acquiring the integrated information embedded in the image, text and hashtags. |
| 關鍵字 | |
| 語言 | en_US |
| 收錄於 | |
| 會議性質 | 國際 |
| 校內研討會地點 | 無 |
| 研討會時間 | 20210423~20210424 |
| 通訊作者 | Ren-Xiang Lin |
| 國別 | IND |
| 公開徵稿 | |
| 出版型式 | |
| 出處 | Smart Innovation, Systems and Technologies |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/128757 ) |