China Conference on Knowledge Graph and Semantic Computing (CCKS 2018)
August 14-17,2018, Tianjin, China
Submission deadline: May 18,2018
CCKS2018(China Conference on Knowledge Graph and Semantic Computing, www.ccks2017.com) is organized by the Technical Committee on Language and Knowledge Computing (http://www.cipsc.org.cn/sigkg/) of The Chinese Information Processing Society of China (http://www.cipsc.org.cn), and is the combination of two conferences: the Chinese Knowledge Graph Symposium (CKGS) and Chinese Semantic Web and Web Science Conference (CSWS). CCKS2016 took place at Xijiao Hotel Beijing, and more than 400 researchers from academia and industry attended the meeting. The theme of CCKS2016 was “Semantic, Knowledge, and Big Linked Data”.
CCKS2018 will be hold on August 14th,2018, Tian Jin, China. The theme is “Knowledge computation, and Language understanding”, discussing key technologies and applications of big data, language understanding, knowledge acquisition, and intelligent service.
The conference welcomes different types of contributions describing new concepts, innovative research work, standards, implementations and experiments, applications, and industrial case studies. Authors are invited to submit complete and unpublished papers, which are not under review in any other conference or journal.
The submissions can be either English or Chinese. All accepted English submissions will be included in an English proceeding published by Springer. Accepted high quality Chinese submissions will be recommended to major Chinese journals such as Journal of Chinese Information Processing (http://www.cipsc.org.cn/jsip/), and Journal of Pattern Recognition and Artificial Intelligence (http://prai.hfcas.ac.cn/), Elsevier Journal of Big Data Research, etc.
All submissions need to go to the submission website: https://easychair.org/conferences/?conf=ccks2017
Knowledge Representation / Ontology Modeling
– Knowledge representation learning/ Knowledge graph embedding
– Distributional representation of knowledge
– Ontology modeling, reuse, and evolution
– Ontology mapping, merging, and alignment
– Ontology evaluation
– Concept learning
– New formalisms (such as probabilistic approaches)
Knowledge Graph Construction / Information Extraction
– Open information extraction
– Crowdsourcing knowledge engineering and collaborative knowledge acquisition
– Human-computer collaboration in knowledge base construction
– Automatic extraction of Wiki data
– Languages, toolkits and systems for automated knowledge base construction
– Supervised, unsupervised ,lightly-supervised learning from text
– Machine reading
Knowledge graph mining
– Classification algorithm
– Link prediction
– Metric learning
– Sorting algorithm
– Clustering algorithm / community detection
– Recommendation algorithm
Semantic integration
– Entity recognition, disambiguation and linking
– Taxonomy integration
– Structure integration
– Heterogeneous knowledge base integration
– Cross lingual knowledge linking and integration
– Ontology based data integration
Knowledge storage , indexing and inference
– Distributed knowledge base systems
– Knowledge query and indexing
– Probabilistic knowledge bases
– Scalable computation; distributed computation
– Graph Database
– Logic-based/probability and statistics-based/Natural Logic-based reasoning
– Reasoning based on embedding and distributed representation
– Rule learning
– Knowledge base completion
Knowledge sharing, reuse and knowledge based system
– Knowledge visualization
– Semantic search
– Knowledge based Q&A
– Intelligent personal assistant system
– Semantic analysis of natural language/audio/video/image
– Demonstrations of existing automatically-built knowledge bases
– Queries on mixtures of structured and unstructured data; querying under uncertainty
– Semantic in big data/social web
Knowledge inference
– Knowledge rule learning
– Knowledge completion
– Knowledge validation
– Reasoning over Semantic Web data
– Document entailment
– Logic-based, embedding-based and other methods for knowledge reasoning
– Representing and reasoning about trust, privacy, and security
Organizer: the Technical Committee on Language and Knowledge Computing (http://www.cipsc.org.cn/sigkg/) of The Chinese Information Processing Society of China (http://www.cipsc.org.cn)
Co-organizer: Tianjin University and Nankai University