Journal Information
World Wide Web
Impact Factor:

Call For Papers
We have witnessed the emergence of a new revolution: `The Web Revolution', which has resulted in the globalization of information access and publishing. World wide web researchers and practitioners face new technical challenges in advancing the world wide web technology from the globalization of access to the globalization of computing.

World Wide Web: Internet and Web Information Systems (WWW) is an international, archival, peer-reviewed journal which covers all aspects of the World Wide Web, including issues related to architectures, applications, Internet and Web information systems, and communities. The purpose of this journal is to provide an international forum for researchers, professionals, and industrial practitioners to share their rapidly developing knowledge and report on new advances in Internet and web-based systems. The journal also focuses on all database- and information-system topics that relate to the Internet and the Web, particularly on ways to model, design, develop, integrate, and manage these systems.

Appearing quarterly, the journal publishes (1) papers describing original ideas and new results, (2) vision papers, (3) reviews of important techniques in related areas, (4) innovative application papers, and (5) progress reports on major international research projects. Papers published in the WWW journal deal with subjects directly or indirectly related to the World Wide Web. The WWW journal provides timely, in-depth coverage of the most recent developments in the World Wide Web discipline to enable anyone involved to keep up-to-date with this dynamically changing technology.

The WWW journal topical coverage includes, but is not restricted to, the following subjects as they relate to the World Wide Web:

Application program interfaces
Authoring tools and environments
Browsing and navigation techniques and tools
Collaborative learning and work
Computer-based training and teaching
Content mark-up languages, such as XML
Courseware development
Data and link management
Data dissemination techniques on the Web
Digital libraries
Distance education
Distributed computing
Electronic commerce
Financial transactions
Information storage and retrieval
Innovative applications
Integration of heterogeneous information sources
Internet and Web-based

    agent systems
    cooperative databases and cooperative information systems
    data management
    database and information-system integration
    information extraction
    information services
    information-system modeling, design, and development
    information visualization
    support tools and languages for information-system development
    search and filtering technology

Internet transactions and transactional processes in the Web
Metrics and measurement
Mobile Web Information Systems
Multimedia software engineering
Object-oriented software engineering
Performance evaluation
Protocols (e.g., HTTP, IIOP)
Real-time computing
Search techniques and engines
Security, authorization, authentication, and privacy
Server and client technologies
Ubiquitous information
Universal design (.e.g., multilingual access)
User interfaces
Verification, validation, and testing
Virtual reality and 3D visualization
Web applications
Web change monitoring and management
Web content standards
Web data mining
Web database security
Web-based data-modeling languages
Web-based GIS
Web Information dynamics
Web information security
Web page design techniques and tools
Web query languages
Web site management techniques and tools
Web-based publishing
Web-based training and teaching
Web-based multimedia/hypermedia systems
Web-supported cooperative work

XML and semi-structured data for Web applications

In addition to the above Internet- and Web-specific topics, the WWW journal also encourages research work on all fundamental issues relating to database and information systems for the Internet and Web. The following are some sample topics of interest when they are addressed within the context of the Internet and Web:

Database and information systems support for cooperative work
Data mining and warehousing
Data models and meta-data management
Information retrieval
Interoperability and heterogeneous information systems
Multimedia database and information systems
Object-oriented and object-relational databases
Query processing
Transaction processing
Workflow systems
Last updated by Dou Sun in 2016-08-12
Special Issues
Special Issue on Deep Mining Big Social Data
Submission Date: 2017-06-30

The internet revolution has made information acquisition easy and cheap so that it has been producing massive web/social data in our real life. The emergence of big social media has lead researchers to study the possibility of their exploitation in order to identify hidden knowledge. However, a huge number of issues appear in obtained big social data. First, there are incomplete social data due to all kinds of reasons, such as security and private information. Second, the structure of social data is different, including structured data (e.g., social web data), semi-structured data (e.g., XML data) and unstructured data (e.g., social networks). Third, the web data are often high-dimensional. However, current computer techniques can only deal with structured, complete and moderate-sized-dimensional data. Moreover, current computer technologies can only mine the basic structure and are not capable of mining their natural complex structure (or deep structure). Hence, there is a huge gap between existing technologies and the real requirements of actual big social data. In this case, deep mining of big social data (such as data preprocessing, deep pattern discovery, pattern fusion, and outlier/noise detection) stands as an interesting promise to relief such a gap. The World Wide Web journal invites papers for a special issue on "Deep Mining Big Social Data" to attract articles that cover existing approaches to mining big social data.
Last updated by Dou Sun in 2017-03-29
Special Issue on Deep vs Shallow: Learning for Emerging Web-scale Data Computing and Applications
Submission Date: 2017-08-15

Today, large collections of web data are explosively created in different fields and have attracted increasing interest in the research community. Big web data can be seen in the social media where thousands of tweets, millions of Facebook "likes", and billions of check-ins on Foursquare are collected to enrich people's daily life. It can also be seen in the finance and business where large amount of stock exchange, online and onsite transactions data flows are captured for inventory monitoring and customer behavior analysis. Big web data provides unprecedented opportunities to address many challenging research problems. Recent success of deep learning has shown that it outperforms state-of-the-art systems in web search, recommendation systems, text analysis, summarization of web data, etc. Therefore, deep learning has a large potential to improve the intelligence of the WWW and the web service systems by efficiently and effectively utilizing big data on the Web. However, deep learning is not omnipotent. Shallow learning is still dominant in fields such as web data storage, real-time computing and association rule mining. It is critical to utilize both deep and shallow learning models to support web-scale data computing and applications. On the other hand, the explosion of big data raises more challenges for learning and puts urgent needs for novel applications. Given the high volume, high velocity, and high variety of big web data that require new forms of processing to enable efficient retrieval, insight discovery and process optimization, there are a lot of research challenges. For example, based on these unprecedented large amount of data, what kinds of novel tools and deployment platforms can be developed to facilitate data storage? This motivates us to design parallel or distributed platforms. Moreover, how do the traditional query and indexing algorithms (proven efficient and effective in small-sized data) be scaled up to millions and even billions of items? The researchers in this topic produced big data indexing techniques as well as using cloud computing. Besides, it is also important to mine useful information and design interesting applications to fully explore the big data treasure. Topics of interest include, but are not limited to: - Big data storage, indexing, and searching - Deep learning for web-scale data analysis - Topics discovering and monitoring from social websites - Indexing algorithms for large-scale web data retrieval - Compression techniques for large-scale multimedia retrieval - Image annotation and classification with deep learning - Clustering for large-scale multimedia data - Knowledge mining from large-scale social media - Storyline summarization for large scale social media - Efficient optimization algorithms for large-scale learning - Algorithms and applications with large-scale social media - Other applications of large scale multimedia data
Last updated by Dou Sun in 2017-06-18
Special Issue on Geo-Social Computing
Submission Date: 2017-10-28

This special issue aims to publish research work that covers the full spectrum of geo-social computing including theoretical, empirical, algorithms, models and design research contributions. The rapid development of Web 2.0, location acquisition and wireless communication technologies has fostered a pro-fusion of geo-social networks, such as location-based social networks (LBSNs) and event-based social networks (EBSNs). LBSNs (e.g., Foursquare, Yelp and Google Place) provide users an online platform to check-in at points of interests (e.g., cinemas, galleries and hotels) and share their life experiences in the physical world via mobile devices. The new dimension of geographical location implies extensive knowledge about an individual's behaviors and interests by bridging the gap between online social networks and the physical world. Moreover, newly emerging EBSNs (e.g., Meetup and Plancast) enable users to check-in and share more specific activities/events held in the physical world, ranging from informal get-togethers (e.g., movie nights and dining out) to formal activities (e.g., culture salons and business meetings). Despite the explosion of interest in social computing, this is the first time to call for papers on geo-social computing. Compared with traditional social computing that only focuses on the social perspective, Geo-Social Computing introduces a new paradigm combining spatial and social dimension. Geo-social computing is fundamentally about computing methods and techniques to understand, model, and facilitate both the social interactions between people and the physical interactions between people and spatial items (e.g., POIs and events). It will bring many benefits to the improved decision making, accurate mobile targeted advertisement, trip planning, richer collaborations, and enhanced problem solving capabilities through a better understanding of human behavior and social interaction in interpersonal, organizational, and societal settings. We welcome submissions that focus on various computation methods and models to exploit and explore the geo-social data generated by both users and GPS devices. Potential topics include but are not limited to the following: - User Profiling - Location-based recommendation - POI Recommendation - Event Recommendation - Community discovery - Social Link Prediction/Friend Recommendation - Information Diffusion in geo-social network - User Mobility Analysis and Modeling - User Linkage Across platforms or devices - Influence Maximization in geo-social networks - Inferring locations of user homes - Inferring Locations of user generated contents (e.g., images, videos and posts) - Collective intelligence - Sentiment Analysis - Spatial data analysis and mining - Team Formation and Collaboration
Last updated by Dou Sun in 2017-06-18
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