Peer recommendation based on comments write on social networks

Social networks and virtual communities has become a popular communication tool among Internet users. Millions of users share publications about different aspects: educational, personal, cultural, etc. Therefore these social sites are rich sources of information about who can help us solve any problems. In this paper, we focus on using the written comments to recommend a person who can answer a request. An automatic analysis of information using text mining techniques was proposed to select the most suitable users. Experimental evaluations show that the proposed techniques are efficient and perform better than a standard search.Eje: XV Workshop de Agentes y Sistemas InteligentesRed de Universidades con Carreras de Informática (RedUNCI

Design principles for competence-based recommender systems

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New forms of collaborative innovation and production on the internet

The Internet has enabled new forms of large-scale collaboration. Voluntary contributions by large numbers of users and co-producers lead to new forms of production and innovation, as seen in Wikipedia, open source software development, in social networks or on user-generated content platforms as well as in many firm-driven Web 2.0 services. Large-scale collaboration on the Internet is an intriguing phenomenon for scholarly debate because it challenges well established insights into the governance of economic action, the sources of innovation, the possibilities of collective action and the social, legal and technical preconditions for successful collaboration. Although contributions to the debate from various disciplines and fine-grained empirical studies already exist, there still is a lack of an interdisciplinary approach

Reputation assessment in collaborative environments.

The popularity of open collaboration platforms is strongly related to the popularity of Internet: the growing of the latter (in technology and users) is a spring to the former. With the advent of Web 2.0, not only the Internet users became from passive receiver of published content to active producer of content, but also active reviewers and editors of content. With the increase of popularity of these platforms, some new interesting problems arise related on how to choose the best one, how to choose the collaborators and how evaluate the quality of the final work. This evolution has brought much benefit to the Internet community, especially related to the availability of free content, but also gave rise to the problem of how much this content, or these people, may be trusted. The purpose of this thesis is to present different reputation systems suitable for collaborative environments; to show that we must use very different techniques to obtain the best from the data we are dealing with and, eventually, to compare reputations systems and recommender systems and show that, under some strict circumstances, they become similar enough and we can just make minor adjustment to one to obtain the other

New forms of collaborative innovation and production on the internet - an interdisciplinary perspective

The Internet has enabled new forms of large-scale collaboration. Voluntary contributions by large numbers of users and co-producers lead to new forms of production and innovation, as seen in Wikipedia, open source software development, in social networks or on user-generated content platforms as well as in many firm-driven Web 2.0 services. Large-scale collaboration on the Internet is an intriguing phenomenon for scholarly debate because it challenges well established insights into the governance of economic action, the sources of innovation, the possibilities of collective action and the social, legal and technical preconditions for successful collaboration. Although contributions to the debate from various disciplines and fine-grained empirical studies already exist, there still is a lack of an interdisciplinary approach