This paper describes a computer simulation of reading that is strongly driven by eye fixation data from human readers. The simulation, READER, is a natural language understanding system that reads a text word by word and whose processing cycles on each word have some correspondence with the human gaze duration on that word. READER operates within a newly developed information processing archite...

Conflict-Free Replicated Data Types (CRDTs) support decentralized collaborative editing of shared data, enabling peer-to-peer sharing and flexible branching merging workflows. While there is extensive work on CRDTs for plain text, much less known about rich text with formatting. No algorithms have been published, existing open-source implementations do not always preserve user intent. In this p...

Collaborative filtering is one of the most popular approaches in recommender systems. In collaborative filtering, the system exploits the ratings of the active user’s like-minded users: his neighbors, to estimate his ratings on the items he has not rated yet and recommend him the items with the highest estimated ratings. Collaborative filtering faces a latency problem: a new item cannot be reco...

Researchers share large amounts of digital resources, which offer new chances for cooperation. Collaborative annotation systems are meant to support this. Often these systems are targeted at a specific task or domain, e.g., annotation of a corpus. The DWAN framework for web annotation is generic and can support a wide range of tasks and domains. A key feature of the framework is its support for...

E-democracy is a cognitive democracy oriented to the extraction and democratization of the knowledge related with the scientific resolution of public decision making problems associated with the governance of society. This paper presents a qualitative approach based in text mining tools to identify voting tendencies from the analysis of the messages and comments elicited by citizens through a c...

The large volume of scientific publications is likely to have hidden knowledge that can be used for suggesting new research topics. We propose an automatic method that is helpful for generating research hypotheses in the field of physics using the massive number of physics journal publications. We convert the text data of titles and abstract sections in publications to a bipartite graph, extrac...