CFP: KARM 2017

official site：http://ada.suda.edu.cn/karm2017/

As the development of World Wide Web, social networking sites, wikis and folksonomies are becoming more and more popular, where the Knowledge Acquisition, Representation and Management (KARM) are the crucial aspects of successful intelligent systems. Knowledge Acquisition is central to the design of cognitive systems. Knowledge should be in a form that allows systems to explain their inferences and accept user feedback. At the same time, knowledge acquisition should exhibit characteristics akin to those of human learning, so that humans can relate to it and be able to interact with it as if it were a knowledgeable colleague. Moreover, the new challenges, problems, and issues have emerged in the context of knowledge representation in Artificial Intelligence (AI), involving the logical manipulation of increasingly large information sets. Furthermore, Knowledge Management stresses the importance of using KM to enhance knowledge production in organizations, not just knowledge sharing or integration. The goal of this workshop is to bring together the researchers involved in the development and application of Knowledge Acquisition, Representation and Management techniques. 

The 1st International Workshop on Knowledge Acquisition, Representation and Management (KARM) with WISE 2017 will bring together the academia, researchers and industrial practitioners from Information Extraction, NLP, Databases, Data Mining and Knowledge Base, and provide a forum for recent advances in the field of Knowledge Graph, Knowledge Acquisition, Knowledge Representation, Graph and Data Management.

Topics

Topics of interest include, but are not limited to the acquisition of the knowledge, the representation of the knowledge in various databases, the management of the knowledge, and the application of semantic-based techniques and technologies in research fields related to (but not limited): 

- Knowledge Graph Management

 - Entity and Relation Extraction 

- Data Cleaning and Data Integration

 - RDF-based Data Representation 

- Graph Management and Search 

- Recommendation System based on Knowledge 

- Privacy Protection in Knowledge Management 

- Spatial and Temporal Data Management

 - Personalized and Context-Aware Ontology 

- Crowdsourcing in Knowledge Management 

- Deep Learning in Knowledge Management

Submissions

 Authors are invited to submit electronically original, English-language research contributions not concurrently submitted elsewhere. Accepted papers will be published by Springer as proceedings in Lecture Notes in Computer Science (LNCS). All submitted papers should be Springer LNCS camera-ready format. The style files are available from Springer LNCS site. All submissions files should be in PDF formats. The number of pages should not exceed 15 pages. Any paper more than 15 pages will be rejected. Please submit your paper(s) at: https://cmt3.research.microsoft.com/KARM2017

Deadline: July 01 2017

Notification: July 25 2017

General Chairs

Kai Zheng, Soochow University 

Lei Zou, Peking University 

Co-Chairs

Zhixu Li, Soochow University

Guanfeng Liu, Soochow University

PC Members

 Ju Fan, Renmin University

 Lei Li, HeFei University of Technology

 Qi Liu, University of Science and Technology of China

 Wei Lu, Renmin University

 Shuai Ma, Beihang University

 Mehmet A. Orgun, Macquarie University

 Tamer Ozsu, University of Waterloo

 Mohamed Sharaf, The University of Queensland

 Yanghua Xiao, Fudan University

 Qing Xie, Wuhan University of Technology

 Jing Yuan, Microsoft Research Asia

 Xiang Zhao, National University of Defence Technology

 Jia Zhu, South China Normal University