Evaluating document filtering systems over time

Evaluating document filtering systems over time

Document filtering is a popular task in information retrieval. A stream of documents arriving over time is filtered for documents relevant to a set of topics. The distinguishing feature of document filtering is the temporal aspect introduced by the stream of documents. Document filtering systems, up to now, have been evaluated in terms of traditional metrics like (microor macro-averaged) precis...

Evaluating collaborative filtering over time

Collaborative Filtering (CF) evaluation centres on accuracy: researchers validate improvements over state of the art algorithms by showing that they reduce the mean error on predicted ratings. However, this evaluation method fails to reflect the reality of deployed recommender systems, which operate algorithms that have to be iteratively updated as new users join the system and more ratings are...

Time-Aware Chi-squared for Document Filtering over Time

Document filtering over time is applied in tasks such as tracking topics in online news or social media. We consider it a classification task, where topics of interest correspond to classes, and the feature space consists of the words associated to each class. In streaming settings the set of words associated with a concept may change. In this paper we employ a multinomial Naive Bayes classifie...

Evaluating the Running Time of Quorum Systems over the Internet

Evaluating Reputation Systems for Document Authenticity

Few P2P file-sharing networks developed to date have successfully provided mechanisms to ensure the authenticity of documents delivered to clients. For example, when a P2P client receives a hit for “Origin of Species,” the client currently has no assurance that the corresponding downloaded document is an authentic copy of Charles Darwin’s work. The document could be a “decoy” and could contain ...