Collaborative Filtering (CF) aims at predicting unknown ratings of a user from other similar users. The uniqueness of the problem has made its formulation distinctive to other information retrieval problems. While the formulation has proved to be effective in rating prediction tasks, it has limited the potential connections between these algorithms and Information Retrieval (IR) models. In this...

Unsolicited bulk e-mail (spam) is a growing problem with tangible costs felt by virtually every Internet user. There are many solutions to this problem, ranging from simple blacklisting to advanced text classification and collaborative filtering. None of these techniques provides a total solution, but new technologies and their application offer increasingly effective filters. This paper provid...

This paper argues for collaborative incremental augmentation of text retrieval as an approach that can be used to immediately show the benefits of relatively heavyweight knowledge formalization in the context of Web 2.0 style collaborative knowledge formalization. Such an approach helps to overcome the “Curse of Prepayment”; i.e. the hitherto necessary very large initial investment in formaliza...

Interaction analysis plays an important role in computer-supported collaborative learning. This paper proposes an interaction analysis model CSCAC composed of three dimensions: group building level, member contribution, member support, which lays the foundation for interaction content analysis. Based on the model and domain ontology, this paper explores the text mining and semantic analysis tec...

Personalized recommender systems can be classified into three main categories: content-based, mostly used to make suggestions depending on the text of the web documents, collaborative filtering, that use ratings from many users to suggest a document or an action to a given user and hybrid solutions. In the collaborative filtering task we can find algorithms such as the naı̈ve Bayes classifier or...

This study investigated the comparative effects of audio-visually prompted collaborative dialogue on the listening comprehension development of symmetrical, asymmetrical, and asymmetrical teacher-fronted EFL learner groups. Besides, it explored the attitude of the participants of the groups concerning the effectiveness of collaborative dialogue for their listening comprehension improvement. The...

We report a first major upgrade of Inforex — a web-based system for qualitative and collaborative text corpora annotation and analysis. Inforex is a part of Polish CLARIN infrastructure1. It is integrated with a digital repository for storing and publishing language resources2 and it allows to visualize, browse and annotate text corpora stored in the repository. As a result of a series of works...

AlvisAE is a text annotation editor aimed at knowledge acquisition projects. An expressive annotation data model allows AlvisAE to support various knowledge acquisition tasks like construction gold standard corpus, ontology population and assisted reading. Collaboration is achieved through a workflow of tasks that emulates common practices (e.g. automatic pre-annotation, adjudication). It is im...

globally, there have been considerable debates on the ethical conduct and review of collaborative international researches. one of the great challenges is to conduct clinical trials in developing countries as externally-sponsored researches (esr). this descriptive survey has reviewed the status of this type of researches in iran during 2002 to 2003. this study was carried out in 44 universities...

This paper presents GATE Teamware – an open-source, web-based, collaborative text annotation framework. It enables users to carry out complex corpus annotation projects, involving distributed annotator teams. Different user roles are provided (annotator, manager, administrator) with customisable user interface functionalities, in order to support the complex workflows and user interactions that...