APWeb-WAIM 2019 : The APWeb-WAIM Joint Conference on Web and Big Data
Call For Papers
The Asia Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint Conference on Web and Big Data is aiming at attracting professionals of different communities related to Web and Big Data who have common interests in interdisciplinary research to share and exchange ideas, experience and the underlying techniques and applications, including Web technologies, database systems, information management, software engineering and big data.
APWeb and WAIM are two separated leading international conferences on research, development and applications of Web technologies and database systems. Previous APWeb conferences were held in Beijing (1998), Hong Kong (1999), Xi’an (2000), Changsha (2001), Xi’an (2003), Hangzhou (2004), Shanghai (2005), Harbin (2006), Huangshan (2007), Shenyang (2008), Suzhou (2009), Busan (2010), Beijing (2011), Kunming (2012), Sydney (2013), Changsha (2014), Guangzhou (2015), and Suzhou (2016). Previous WAIM conferences were held in Shanghai (2000), Xi’an (2001), Beijing (2002), Chengdu (2003), Dalian (2004), Hangzhou (2005), Hong Kong (2006), Huangshan (2007), Zhangjiajie (2008), Suzhou (2009), Jiuzhaigou (2010), Wuhan (2011), Harbin (2012), Beidaihe (2013), Macau (2014), Qingdao (2015), and Nanchang (2016).
Starting in 2017, the two conference committees have agreed to launch a joint conference. With the increased focus on Big Data, the new joint conference is expected to attract more professionals from different industrial and academic communities, not only from the Asia Pacific countries but also from other continents.
The third APWeb-WAIM joint conference on Web and Big Data 2019 will take place in Chengdu, China. Chengdu is the capital of Sichuan Province and it is one of the famous historical and cultural cities in southwestern China. It is our sincere hope that you will make best of your time here to visit more places and enjoy more scenery and we believe you will harvest a lot.
● Abstract Deadline: February 14th, 2019 (PST)
● Full Paper Deadline: February 14th, 2019 (PST)
● Author Notification: April 28th, 2019
● Camera Ready Deadline: May 15th, 2019
The APWeb-WAIM Joint Conference on Web and Big Data 2019 covers but is not limited to the following topics:
● Advanced database and Web applications
● Big data analytics
● Big data management
● Caching and replication
● Cloud computing
● Content management
● Data and information quality
● Data management for mobile and pervasive computing
● Data management on new hardware
● Data mining
● Data provenance and workflow
● Data warehousing and OLAP
● Deep Web
● Digital libraries
● Entity resolution and entity linking
● Graph data management, RDF, social networks
● Information extraction
● Information integration and heterogeneous systems
● Information retrieval
● Knowledge extraction and management
● Multimedia information systems
● Machine Learning
● Parallel and distributed data management
● Query processing and optimization
● Recommender systems
● Security, privacy, and trust
● Semantic Web and ontology
● Sensor networks
● Service-oriented computing
● Social media
● Spatial and temporal databases
● Storage and access methods
● Streams, complex event processing
● Text database, keyword search
● Uncertain data
● Web advertising and community analysis
● Web information quality and fusion
● Web search and meta-search
● Web service management
● XML and semi-structured data
The proceedings of APWEB/WAIM 2019 will be published by Springer in the Lecture Notes in Computer Science (LNCS) series, one volume for the main conference and one volume for the workshops. Both will be indexed by EI. All the best papers and a few selected papers will be recommended to special issues of World Wide Web: Internet and Web Information Systems (WWWJ), and Data Science and Engineering (DSE).
Submissions must not exceed 15 pages in LNCS format, including references. All submissions must be in PDF format. Authors should avoid the use of non-English fonts to avoid problems with printing and viewing the submissions. All accepted papers MUST follow strictly the instructions for LNCS Authors. Springer LNCS site offers style files and information: http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0p
APWEB/WAIM 2019 will employ double-blind reviewing process. Every research paper submitted to APWEB/WAIM 2019 will undergo a "double-blind" reviewing process: the PC members and referees who review the paper will not know the identity of the authors. To ensure anonymity of authorship, authors must prepare their manuscript as follows:
● Authors' names and affiliations must not appear on the title page or elsewhere in the paper.
● Funding sources must not be acknowledged on the title page or elsewhere in the paper.
● Research group members, or other colleagues or collaborators, must not be acknowledged anywhere in the paper.
● The paper's file name must not identify the authors of the paper. It is strongly suggested that the submitted file be named with the assigned submission number. For example, if your assigned paper number is 352, then name your submission file 352.pdf.
● Source file naming must also be done with care, to avoid identifying the authors' name in the paper's associated metadata. For example, if your name is Jane Smith and you submit a PDF file generated from a .dvi file called Jane-Smith.dvi, your authorship could be inferred by looking into the PDF file.
It is the responsibility of authors to do their very best to preserve anonymity. Papers that do not follow the GUILDLINES here, or otherwise potentially reveal the identity of the authors, are subject to immediate rejection.
All papers should be submitted through the Conference Management Tool at:
Heng Tao Shen (University of Electronic Science and Technology of China, China)
Kotagiri Ramamohanarao (University of Melbourne, Australia)
Jiliu Zhou (Chengdu University of Information Technology, China)
Program Committee Co-Chairs
Jie Shao (University of Electronic Science and Technology of China, China)
Man Lung Yiu (Hong Kong Polytechnic University, HK)
Masashi Toyoda (University of Tokyo, Japan)