图 书 馆
基于协作助推的微博活动分类Collaborative Boosting for Activity Classification in Microblogs |
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| 课程网址: | http://videolectures.net/kdd2013_lu_link_microblogs/ |
| 主讲教师: | Zhengdong Lu |
| 开课单位: | 香港科技大学 |
| 开课时间: | 2013-09-27 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Users' daily activities, such as dining and shopping, inherently reflect their habits, intents and preferences, thus provide invaluable information for services such as personalized information recommendation and targeted advertising. Users' activity information, although ubiquitous on social media, has largely been unexploited. This paper addresses the task of user activity classification in microblogs, where users can publish short messages and maintain social networks online. We identify the importance of modeling a user's individuality, and that of exploiting opinions of the user's friends for accurate activity classification. In this light, we propose a novel collaborative boosting framework comprising a text-to-activity classifier for each user, and a mechanism for collaboration between classifiers of users having social connections. The collaboration between two classifiers includes exchanging their own training instances and their dynamically changing labeling decisions. We propose an iterative learning procedure that is formulated as gradient descent in learning function space, while opinion exchange between classifiers is implemented with a weighted voting in each learning iteration. We show through experiments that on real-world data from Sina Weibo, our method outperforms existing off-the-shelf algorithms that do not take users' individuality or social connections into account. |
| 关 键 词: | 微博信息; 活动分类; 个性推荐; 定向广告 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-05-29：chenxin01 |
| 最后编审: | 2023-05-29：chenxin01 |
| 阅读次数: | 23 |