SABINE:一个语义注释社交内容的多用途数据集SABINE: A Multi-Purpose Dataset of Semantically-Annotated Social Content |
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课程网址: | http://videolectures.net/iswc2018_ferrara_sabine_multi_purpose/ |
主讲教师: | Alfio Ferrara |
开课单位: | 米兰大学 |
开课时间: | 2018-11-22 |
课程语种: | 其它 |
中文简介: | 社交商业智能(SBI)是一门将企业数据与社交内容相结合的学科,让决策者分析从环境中感知的趋势。SBI在几个领域提出了研究挑战,如IR、数据挖掘和NLP;不幸的是,SBI的研究往往受到缺乏可公开获得的真实世界数据来进行实验方法的限制,以及难以确定基本事实的限制。为了填补这一空白,我们提出了SABINE,这是欧洲政治领域的一个模块化数据集。SABINE包括从5万个网络资源中抓取的600万个双语剪辑,每个剪辑都与元数据和情感得分有关;一个包含400个主题的本体,它们在剪辑中的出现,以及它们到DBpedia的映射;两个多维立方体,用于分析和聚合情感和语义事件。我们还提出了一系列可以使用SABINE解决的研究挑战;值得注意的是,专家验证的基本事实的存在确保了对整个履行机构进程以及每一项任务测试方法的可能性。 |
课程简介: | Social Business Intelligence (SBI) is the discipline that combines corporate data with social content to let decision makers analyze the trends perceived from the environment. SBI poses research challenges in several areas, such as IR, data mining, and NLP; unfortunately, SBI research is often restrained by the lack of publicly-available, real-world data for experimenting approaches, and by the difficulties in determining a ground truth. To fill this gap we present SABINE, a modular dataset in the domain of European politics. SABINE includes 6 millions bilingual clips crawled from 50 000 web sources, each associated with metadata and sentiment scores; an ontology with 400 topics, their occurrences in the clips, and their mapping to DBpedia; two multidimensional cubes for analyzing and aggregating sentiment and semantic occurrences. We also propose a set of research challenges that can be addressed using SABINE; remarkably, the presence of an expert-validated ground truth ensures the possibility of testing approaches to the whole SBI process as well as to each single task. |
关 键 词: | 社交商业智能; 数据挖掘; 聚合情感 |
课程来源: | 视频讲座网 |
数据采集: | 2023-03-16:chenjy |
最后编审: | 2023-05-11:chenjy |
阅读次数: | 26 |