Web social media presents challenging knowledge management issues at all levels – for individuals, organizations, communities, business, and governments. Knowledge management is the process of capturing, developing, sharing, and effectively using organisational knowledge. Web social media is different from traditional or industrial media in many ways, including quality, reach, frequency, usability, immediacy, and permanence. Such characteristics have made knowledge management on web social media more challenging than ever before. Breakthroughs need to be made on many technological bottlenecks, such as; i) how to gain the capability of dealing with an incredible volume of information; ii) how to overcome the difficulty of extracting relevant knowledge from the information deluge; iii) how to not only manage information but also make it productive; and iv) how to transit valuable information into business value. The challenges and potential benefits of knowledge management of web social media have attracted much attention from the researchers to make many great achievements in recent years.
Topics include but are not limited to:
Big Data, Cloud Computing, Streams in terms of Social Media
Clustering, Classification, and Ranking of Social Media Data
Data Mining Theory, Methods, and Applications on Social Media
Social Media Information Extraction and Filtering
Knowledge Representation, Reasoning, and Visualisation
Large-Scale Machine Learning, Optimisation, and Statistical Techniques
Personalisation, Recommendation, Advertising, and Search in Social Media
Privacy and Security in Social Media
Semantic Understanding and Entity Extraction in Social Media
Social Media and Social Networks
Spatial, Temporal, and Graph Data Mining in Social Media
Text, Multimedia, and Web Data Mining
Time-Series, Rule, and Pattern Mining on Social Media Data
08月23日
2017
08月26日
2017
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