Many collaborative systems use text as the primary modality and only use multimedia via attachments. MuSwikis are a collaboration system where graphics are the primary modality, and text is treated just like any other graphical element. This paper describes the MuSwiki system for the first time, describes a pilot study that was run on MuSwikis, and discusses ideas generated from that study.

In this paper, we describe how we are using text mining solutions to enhance the production of systematic reviews. This collaborative project also serves as a proof of concept and as a testbed for deriving requirements for the development of more generally applicable text mining tools and services.

Real-time collaborative editors, like GoogleDocs or Etherpad, allow the simultaneous edition of adocument by several users. These applications need to replicate the edited document, for the so calledreal-time purpose of permitting a fast and reactive editing by any user at any time. Editing conflictsfrequently occur, and must be automatically handled by the application, in order to ...

Wikis are promoted as collaborative writing tools that allow students to transform a text into a collective document by information sharing and group reflection. However, despite the promising collaborative capabilities of wikis, their pedagogical value regarding collaborative writing is still questionable. Wiki alone cannot make collaborative writing happen, and students do not automatically b...

Clustering is a widely studied data mining problem in the text domains. The problem finds numerous applications in customer segmentation, classification, collaborative filtering, visualization, document organization, and indexing. In this chapter, we will provide a detailed survey of the problem of text clustering. We will study the key challenges of the clustering problem, as it applies to the...

Clustering is a widely studied data mining problem in the text domains. The problem finds numerous applications in customer segmentation, classification, collaborative filtering, visualization, document organization, and indexing. In this chapter, we will provide a detailed survey of the problem of text clustering. We will study the key challenges of the clustering problem, as it applies to the...

We propose a generative model for text and other collections of discrete data that generalizes or improves on several previous models including naive Bayes/unigram, mixture of unigrams [6], and Hofmann's aspect model , also known as probabilistic latent semantic indexing (pLSI) [3]. In the context of text modeling, our model posits that each document is generated as a mixture of topics, where t...

We examine deployment strategies for text translation and text summarization tasks. We formalize a deployment strategy along three dimensions: work structure, workforce organization, and work style. Work structure can be either simultaneous or sequential, workforce organization independent or collaborative, and work style either crowd-only or hybrid. We use Amazon Mechanical Turk to evaluate th...

Language Resources are recognized as an essential component in linguistic infrastructure and a starting point of Natural Language Processing systems and applications. In this paper, we describe the achievement of the development and the use of Thai Language Resources germinated with an open collaboration platform, under the collaboration between research institutes. The resources include either...

This paper focuses on information retrieval aspects of a new application in domain of collaborative systems based on utilization of semantic principles for representation of different types of knowledge, collaborative objects and relations between them. Proposed collaborative system (within European IST project called KP-Lab1) uses ontologies as common communication framework and exchange forma...