- Wenhui (Wendy) Liao (Thomson Reuters, MN, USA)
- Masoud Makrehchi (University of Ontario Institute of Technology, ON, Canada)
Web 2 has revolutionized our daily online experience. The two major characteristics of Web 2 are social interaction and sharing. Users can interact with other users and social groups over their interests. Web 2 also let people share their content (tags, video, photo, blog, bookmark, profile, and so on) and also their connections. On important feature of social web to support the two characteristics is social recommendation.
Social recommendation can be defined in two scenarios. First, it is the task of recommending relevant social entities to the users. For example, user to user recommendation (link recommendation), user to community, and community to user recommendation. Second, recommending non-social entities (such as products) by mining social interaction data. The main objective of this workshop is to address these two scenarios in social recommendation, gather researchers working on different social recommendation problems, and create an opportunity to exchange ideas and also future collaborations among researchers.
- Adam Wierzbicki (Polish-Japanese Institute of Information Technology, Poland)
Open Collaboration over the Internet ranges from simple tasks, such as used in crowdsourcing on Amazon Mechanical Turk, to more complex ones, such as writing articles on Wikipedia, writing open source software (F/OSS), or solving scientific problems (Innocentive). All Open Collaboration projects and applications have the following common characteristics: they require adequate motivation of users to succeed; they need a method for managing the quality of contributions, and they are coordinated efforts. The required coordination increases with the increasing complexity of the collaborative task: for Amazon Mechanical Turk, the coordination is simple, while for writing F/OSS software, it is much more complex. The understanding of motivation for contributions to Open Collaboration projects requires interdisciplinary research that combines expertise from computer and social science, as well as the law, management science and economics. The goal of the workshop is to gather ideas and research experience from diverse areas of research, such as research on crowdsourcing, on F/OSS software or on the Wikipedia knowledge community.
- Adam Jatowt (Kyoto University, Japan)
- Gaël Dias (Normandie University, France)
- Agostini-Ouafi Viviana (Normandie University, France)
- Christian Gudehus (University of Flensburg, Germany)
- Günter Mühlberger (University of Innsbruck, Austria)
The 1st International Workshop on Histoinformatics aims at fostering the interaction between Computer Science and Historical Science. This interdisciplinary initiative is a response to the growing popularity of Digital Humanities and an increased tendency to apply computer techniques for supporting and facilitating research in Humanities. Nowadays, due to the increasing activities in digitizing and opening historical sources, the Science of History can greatly benefit from the advances of Computer and Information sciences which consist of processing, organizing and making sense of data and information. As such, new Computer Science techniques can be applied to verify and validate historical assumptions based on text reasoning, image interpretation or memory understanding. Our objective is to provide for the two different research communities a place to meet and exchange ideas and to facilitate discussion. We hope the workshop will result in a survey of current problems and potential solutions, with particular focus on exploring opportunities for collaboration and interaction of researchers working on various subareas within Computer Science and History Sciences. The main topics of the workshop are that of supporting historical research and analysis through the application of Computer Science theories or technologies, analyzing and making use of historical texts, recreating past course of actions, analyzing collective memories, visualizing historical data, providing efficient access to large wealth of accumulated historical knowledge and so on.