OpenRaiser/Intern-Atlas huggingface dataset:
Iterative Discriminant Tensor Factorization for Behavior Comparison in Massive Open Online Courses
Authors: Xidao Wen, Yu-Ru Lin, Xi Liu, Peter Brusilovsky, Jordan Barria-Pineda
Venue: WWW
Year: 2019

The increasing utilization of massive open online courses has significantly expanded global access to formal education. Despite the technology's promising future, student interaction on MOOCs is still a relatively under-explored and poorly understood topic. This work proposes a multi-level pattern discovery through hierarchical discriminative tensor factorization. We formulate the problem as a hierarchical discriminant subspace learning problem, where the goal is to discover the shared and discriminative patterns with a hierarchical structure. The discovered patterns enable a more effective exploration of the contrasting behaviors of two performance groups. We conduct extensive experiments on several real-world MOOC datasets to demonstrate the effectiveness of our proposed approach. Our study advances the current predictive modeling in MOOCs by providing more interpretable behavioral patterns and linking their relationships with the performance outcome.
The Challenge of API Management: API Strategies for Decentralized API Landscapes
Authors: Erik Wilde, Mike Amundsen
Venue: WWW
Year: 2019

The Web as the world’s largest information system has largely settled on a solid foundation of HTTP-based connectivity, and the representation of User Interface (UI) information resources through a mix of HTML and scripting. In contrast, the similarly rapidly evolving “Web of Services” is still based on a more diverse and more quickly evolving set of approaches and technologies. This can make architectural decisions harder when it comes to choosing on how to expose information and services through an Application Programming Interface (API). This challenge becomes even more pronounced when organizations are faced with developing strategies for managing constantly growing and evolving API landscapes. This tutorial takes participants through two different journeys. The first one is a journey discussing API styles and API technologies, comparing and contrasting them as a way to highlight the fact that there is no such thing as the one best choice. The goal of this first journey is to provide an overview of how APIs are used nowadays in research and in industry. The second journey discusses the question of how to define an API strategy, which focuses both on helping teams to make effective choices about APIs in a given context, and on how to manage that context over time when large organizations nowadays have thousands of APIs, which will continue to evolve constantly.
Semi-supervised Multi-view Individual and Sharable Feature Learning for Webpage Classification
Authors: Fei Wu, Xiao-Yuan Jing, Jun Zhou, Yi-mu Ji, Chao Lan, Qinghua Huang, Ruchuan Wang
Venue: WWW
Year: 2019

Semi-supervised multi-view feature learning (SMFL) is a feasible solution for webpage classification. However, how to fully extract the complementarity and correlation information effectively under semi-supervised setting has not been well studied. In this paper, we propose a semi-supervised multi-view individual and sharable feature learning (SMISFL) approach, which jointly learns multiple view-individual transformations and one sharable transformation to explore the view-specific property for each view and the common property across views. We design a semi-supervised multi-view similarity preserving term, which fully utilizes the label information of labeled samples and similarity information of unlabeled samples from both intra-view and inter-view aspects. To promote learning of diversity, we impose a constraint on view-individual transformation to make the learned view-specific features to be statistically uncorrelated. Furthermore, we train a linear classifier, such that view-specific and shared features can be effectively combined for classification. Experiments on widely used webpage datasets demonstrate that SMISFL can significantly outperform state-of-the-art SMFL and webpage classification methods.
Dynamic Ensemble of Contextual Bandits to Satisfy Users' Changing Interests
Authors: Qingyun Wu, Huazheng Wang, Yanen Li, Hongning Wang
Venue: WWW
Year: 2019

Recommender systems have to handle a highly non-stationary environment, due to users' fast changing interests over time. Traditional solutions have to periodically rebuild their models, despite high computational cost. But this still cannot empower them to automatically adjust to abrupt changes in trends caused by timely information. It is important to note that the changes of reward distributions caused by a non-stationary environment can also be context dependent. When the change is orthogonal to the given context, previously maintained models should be reused for better recommendation prediction. In this work, we focus on contextual bandit algorithms for making adaptive recommendations. We capitalize on the unique context-dependent property of reward changes to conquer the challenging non-stationary environment for model update. In particular, we maintain a dynamic ensemble of contextual bandit models, where each bandit model's reward estimation quality is monitored regarding given context and possible environment changes. Only the admissible models to the current environment will be used for recommendation. We provide a rigorous upper regret bound analysis of our proposed algorithm. Extensive empirical evaluations on both synthetic and three real-world datasets confirmed the algorithm's advantage against existing non-stationary solutions that simply create new models whenever an environment change is detected.
Deep Chit-Chat: Deep Learning for Chatbots
Authors: Wei Wu, Rui Yan
Venue: WWW
Year: 2019

The tutorial is based on our long-term research on open domain conversation and rich hands-on experience on development of Microsoft XiaoIce. We will summarize the recent achievements made by both academia and industry on chatbots, and give a thorough and systematic introduction to state-of-the-art methods for open domain conversation modeling including both retrieval-based methods and generation-based methods. In addition to these, our tutorial will also cover some new trends of research of chatbots, such as how to design a reasonable evaluation metric for open domain dialogue generation, how to build conversation models with multiple modalities, and how to conduct dialogue management in open domain conversation systems.
Attention - from Neuroscience to the Web and Wellbeing
Venue: WWW
Year: 2019

It is our great pleasure to welcome you to the first multi-disciplinary workshop on “Attention from Neuroscience to the Web and Wellbeing”, at the Web Conference 2019. In an age where multiple apps, advertisements and an abundance of social media are vying to get the user’s attention, attention has become an extremely scarce resource. Never before has attention economy been more acute. Designing effective solutions that are mindful of user’s attention call for better understanding of attention -how it works in the brain, how it can be measured at scale on the web, and its current applications as well as challenges.
5th AW4City 2019 Chairs' Welcome
Venue: WWW
Year: 2019

It is our great pleasure to welcome you to the AW4City 2019 5 International Workshop on Web Applications and Smart Cities. This year’s fifth AW4City version follows up the success of the previous four events and emphasizes on the contribution of web applications and Apps to urban mobility. In the era of cities and under the UN 2030 Agenda for sustainable growth, cities are making an important shift regarding thinking of compact cities and they develop sustainable mobility plans. Issues like parking, traffic congestion and safety, sharing transportation and smart parking are among the topics where governments and the industry direct smart services, while data collection and analysis enable government’s fast –or even real-timedecision-making for alternative transportation means’ deliberation, public transportation changes, urban planning etc., and new business models appear that utilize platforms and data. Additionally, new types of business in transportation appear (e.g., that utilize sensors and big data), while things’ transportation is another challenge that cities have been started phasing.
Data Science for Social Good Chairs' Welcome
Venue: WWW
Year: 2019

The need for social innovation is clear: From climate change to income inequality to geopolitical upheaval and terrorism, the difficulties confronting us are unprecedented not only in their variety but also in their complexity. At the same time, today’s public policy practices and tools are not sufficient. Increasingly, it is clear, we need not only new solutions but new methods to arriving at solutions. Data and data science will become more central to meeting these challenges and to social innovation, philanthropy, international development and humanitarian aid. From the analysis of satellite imagery to mapping poverty to using Facebook data to track the global digital gender gap, “Data Science for Social Good” provides great promise. Data from corporate actors (e.g. mobile phones data, remote sensing, satellite imagery) as well as data from digital traces generated by the pervasiveness of the Web in combination with state-of-the-art knowledge generated by data science can be synergically exploited to solve issues around many social problems and support global agencies and policymakers in implementing better and more impactful policies and interventions.
DL4G-SDE 2019 Chairs' Welcome
Venue: WWW
Year: 2019

The call for papers attracted submissions from the United States, Europe, Asia and Australia. Each submission was reviewed by two to three reviewers. After a rigorous reviewing process, we were able to accept 9 papers (4 as regular papers for oral presentation and 5 as poster presentations that cover ongoing or recently-published work). In addition, the workshop features three keynotes delivered by leading experts in representation learning on graphs and structured data from both academia and industry:
First International Workshop on e-Commerce and NLP (ECNLP) Chairs' Welcome
Venue: WWW
Year: 2019

This workshop focuses on intersection of Natural Language Processing (NLP) and e-Commerce. NLP and information retrieval (IR) have been powering e-Commerce applications since the early days of the fields. Today, NLP and IR already play a significant role in e-Commerce tasks, including product search, recommender systems, product question answering, machine translation, sentiment analysis, product description and review summarization, and customer review processing. With the exploding popularity of chatbots and shopping assistants – both textand voice-based – NLP, IR, question answering, and dialogue systems research is poised to transform e-Commerce once again.
Emoji2019 Workshop Chairs' Welcome
Venue: WWW
Year: 2019

It is our great pleasure to welcome you to Emoji2019: The 2 International Workshop on Emoji Understanding and Applications in Social Media at WWW 2019. With the rise of social media, emoji has become a popular and an indispensable form of online communication. Emojis have been widely used to enhance the sentiment, emotion, and sarcasm expressed online. As emojis offer a primary method for more expressive online communication, it is essential to investigate how they can be used to improve computer-mediated communication. However, the ability to automatically process, derive meaning, and interpret text fused with emoji is challenged by the pictorial nature of emoji, the fact that the same emoji may be used in different contexts to express different meanings, and that in different cultures and communities over the world the same emoji representation may be interpreted differently. This makes it especially difficult to apply traditional Natural Language Processing techniques to analyze them. The Emoji2019 workshop seeks to provide a forum to bring together researchers and practitioners from both academia and industry in the areas of computer science, social network analysis and mining, natural language processing, computational linguistics, human-computer interaction, and computational social sciences to discuss high-quality research and emerging applications, to exchange ideas and experience, and to identify new opportunities for collaboration towards solving the above challenges.
FATES on the WEB Chairs' Welcome
Venue: WWW
Year: 2019

We would like to sincerely thank The Web Conference organization for the constant help and support, the Program Committee members and reviewers for their excellent work and invaluable support during the review process, and the authors of the submitted papers for their very interesting and high-quality contributions. We also thank the ACM team for the proceedings. Most importantly, we thank all the attendees who ensure 'FATES on the Web' could be an appropriate forum of knowledge and experiences sharing about the new challenges in Social Web.
Augmenting Intelligence with Bias-aware Humans-in-the-loop (HumBL2019)
Venue: WWW
Year: 2019

It is our great pleasure to welcome you to the WWW 2019 Augmenting Intelligence with Bias-aware Humans-in-the-loop (HumBL2019) . The goal of this workshop is to bring together researchers and practitioners in various areas of AI (i.e., Machine Learning, NLP, Computational Advertising, etc.) and crowdsourcing, to explore new pathways of the human-in-the-loop paradigm and disentangle the relationship between crowdsourcing and bias management. We aim to discuss methods where the user has the ability to heavily influence the outcome of the process by providing feedback to the system, as well as the opportunity to grab different perspectives about the underlying domain and understand the step by step machine process leading to a certain outcome. Additionally, we focus on one of the major concerns in AI research: being able to explain and understand the results as well as identifying, avoiding and/or mitigating bias in the underlying data that might lead to unfair or unethical conclusions . Bringing humans and machines together creates a natural symbiosis for accurate interpretation of data at scale. We focus on the partnership between humans and machines in social computing systems, with a special emphasis on human factors and ethics of crowdsourcing techniques , and a wide-range of domain applications , such as healthcare, NLP technologies, translation, data quality control and sentiment analysis. As human-in-the-loop processes are intrinsically related to machine learning , we consider solutions that deal with sparse and noisy annotated data, as well as workflows with crowd-supported active learning. Additionally, we address challenges in the crowdsourced data collection process, including task design, collecting data while respecting privacy constraints and dealing with multi-linguality. Finally, we discuss the different types of bias in crowdsourcing (e.g., gender-related, cultural, cognitive, experience and knowledge bias) that can occur in different steps of the crowdsourcing process, from recruiting and task selection to result aggregation, and analyse methods to monitor and mitigate biases in algorithmic systems through crowdsourcing, as it can help diversify sources of information.
First Workshop on Hypermedia Multi-Agent Systems (HyperAgents 2019) Workshop Chairs' Welcome & Organization Listing
Venue: WWW
Year: 2019

Hypermedia is increasingly used in Web service design, particularly in Web of Things and Linked Data systems: the dynamic and open nature of these systems requires components to be deployed and to evolve independently from one another, which makes the use of static Web APIs that are manually integrated by developers simply impractical (in any such systems). This evolution raises new challenges: to discover, consume, and integrate hypermedia APIs at runtime, clients have to become increasingly autonomous in pursuit of their design goals. Such autonomous systems have been studied to a large extent in research on multi-agent systems (MAS). To consolidate the evolution of hypermedia APIs, it is now necessary to have comprehensive discussions on integrating hypermedia systems and MAS, which we call Hypermedia MAS.
The First International Workshop on Knowledge Graph Technology and Applications Chairs' Welcome
Venue: WWW
Year: 2019

Computational Methods about Knowledge
LA-Web 2019 Chairs' Welcome
Venue: WWW
Year: 2019

LA-WEB was born in 2003 as an international scientific venue that aims towards gathering the community of Web researchers and practitioners worldwide, working on topics of importance to the Latin American region. In addition, this year we have extended LA-WEB's scope to also include Web-centered research from Latin American institutions and from Latin American authors around the world. We expect that the combination of LA-WEB and The Web Conference will create a synergetic atmosphere between the Latin American Web community and the global community of leading Web researchers.
LocWeb2019 Chairs' Welcome
Venue: WWW
Year: 2019

We are excited to welcome you to the 9 International Workshop on Location and the Web (LocWeb2019) at WWW 2019. LocWeb 2019 will continue the workshop series at the intersection of location-based services and Web architecture. It focuses on Web-scale services and systems facilitating location-aware information access as well as on Spatial Social Behavior Analytics on the Web as part of social computing.
MDML'2019 Chairs' Welcome
Venue: WWW
Year: 2019

research-article Share on MDML '™2019 Chairs' WelcomeWWW '19: Companion Proceedings of The 2019 World Wide Web ConferenceMay 2019 Pages 928–929https://doi.org/10.1145/3308560.3316533Published:13 May 2019Publication History 0citation43DownloadsMetricsTotal Citations0Total Downloads43Last 12 Months3Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
MEPDaW Chairs' Welcome
Venue: WWW
Year: 2019

We received 6 submissions from all around the world covering a broad range of topics. We evaluated them regarding relevance, quality, and novelty, selecting 5 papers. We invited 2 extended abstracts from the recent Special Issue of the Journal of Web Semantics on Managing the Evolution and Preservation of the Data Web (January 2019). In addition, Laure Berti-Équille will give an inspiring talk, and we will close the workshop with a plenary discussion. Thus, MEPDaW includes the following talks:
MisInfo '19 Chairs' Welcome
Venue: WWW
Year: 2019

It is our great pleasure to welcome you to the First International Workshop on Misinformation, Computational Fact-Checking and Credible Web at TheWebConf 2019. It is a recognized problem that our society is struggling with an unprecedented amount of falsehood that harms wealth, democracy, and health. Debunking misinformation and disinformation calls for interdisciplinary collaboration of and advancements in multiple areas, including journalism, communication studies, law and public policy, psychology, and political science. Computing technology plays a crucial role in it. The last few years have witnessed a substantial growth in efforts at computational fact-checking, of which many are data-driven, AI-powered, and include human in the loop. These efforts tackle various fronts, such as the detection of fabricated news, rumors, and spam on social media, automation in fact-checking, flagging clickbait articles, and discovering fake accounts and malicious social media bots, but are far from the maturity that is required to reach commercial application.
International Workshop on Modeling Social Media (MSM'2019) Chairs' Welcome
Venue: WWW
Year: 2019

Welcome to the TheWebConf 2019 International Workshop on Modeling Social Media (MSM'2019) Mining, Modeling and Learning from Social Media. We are celebrating our 10 edition (one decade) of our workshop. Social networks such as Facebook, Twitter, and LinkedIn generate huge amounts of data that require the application of big data analytics to produce meaningful information to both information consumers and data generators. Machine learning and AI techniques are particularly effective in situations where deep and predictive insights need to be uncovered from such social media data sets that are large, diverse and fast changing.
Workshop on Subjectivity, Ambiguity and Disagreement on the Web (SAD2019)
Venue: WWW
Year: 2019

, systems and
TempWeb 2019 Chairs' Welcome
Venue: WWW
Year: 2019

Time is a key dimension to understand the Web. It is fair to say that it has not received yet all the attention it deserves and TempWeb is an attempt to help remedy this situation by putting time as the center of its reflection. Studying time in this context actually covers a large spectrum, from the extraction of temporal information and knowledge, to diachronic studies for the design of infrastructural and experimental settings enabling a proper observation of this dimension.
Wiki Workshop Chairs' Welcome
Venue: WWW
Year: 2019

It is our great pleasure to welcome you to the ​Wiki Workshop at the Web Conference 2019​. The goal of this workshop is to bring together researchers exploring all aspects of Wikimedia projects such as Wikipedia, Wikidata, and Wikimedia Commons. With members of the Wikimedia Foundation’s Research team on the organizing committee and with the experience of successful workshops in 2015, 2016, 2017, and 2018 we aim to continue facilitating a direct pathway for exchanging ideas between the organization that coordinates Wikimedia projects and the researchers interested in studying them.
The Third Workshop on Women in Web Data Science (WinDS '19) Chairs' Welcome & Organization Listing
Venue: WWW
Year: 2019

It is our great pleasure to welcome you to the WWW 2019 Third Women in Web Data Science (WinDS’19) Workshop. This half-day workshop brings together female faculties, graduate students, research scientists, and industry researchers for an opportunity to connect, exchange ideas, and learn from each other in the field of Data Science. Underrepresented minorities, graduates, and undergraduates interested in pursuing data science and machine learning research are encouraged to participate. While most presenters are women, everybody is invited to attend.
Understanding Urban Dynamics via State-sharing Hidden Markov Model
Authors: Tong Xia, Yue Yu, Fengli Xu, Funing Sun, Diansheng Guo, Depeng Jin, Yong Li
Venue: WWW
Year: 2019

Modeling people's activities in the urban space is a crucial socio-economic task but extremely challenging due to the deficiency of suitable methods. To model the temporal dynamics of human activities concisely and specifically, we present State-sharing Hidden Markov Model (SSHMM). First, it extracts the urban states from the whole city, which captures the volume of population flows as well as the frequency of each type of Point of Interests (PoIs) visited. Second, it characterizes the urban dynamics of each urban region as the state transition on the shared-states, which reveals distinct daily rhythms of urban activities. We evaluate our method via a large-scale real-life mobility dataset and results demonstrate that SSHMM learns semantics-rich urban dynamics, which are highly correlated with the functions of the region. Besides, it recovers the urban dynamics in different time slots with an error of 0.0793, which outperforms the general HMM by 54.2%.