Social media are pervaded by unsubstantiated or untruthful rumors, that contribute to the alarming phenomenon of misinformation. The widespread presence of a heterogeneous mass of information sources may affect the mechanisms behind the formation of public opinion. Such a scenario is a florid environment for digital wildfires when combined with functional illiteracy, information overload, and c...

In this paper, we present a fast and scalable Spreading Activation Network (SAN) framework for improving weakly annotated data which is typically generated by an automated information extraction system from Web documents. Weakly annotated data suffers from two major problems; (i) might contain incorrect ontological role assignments, and (ii) might have many missing attributes. The SAN model des...

Most AI simulations have modeled memory retrieval separately from comprehension, even though both activities seem to use many of the same processes. We have developed REMIND, a model that performs both episodic memory retrieval and language understanding with a single spreading-activation mechanism. This approach has a number of advantages over retrieval-only models. First, because the comprehe...

Identifying topics and concepts associated with a set of documents is a task common to many applications. It can help in the annotation and categorization of documents and be used to model a person's current interests for improving search results, business intelligence or selecting appropriate advertisements. One approach is to associate a document with a set of topics selected from a fixed ont...

Neurocognitive processes responsible for representation of meaning and understanding of words are investigated. First a review of current knowledge about word representation, recent experiments linking it to associative memory and to right hemisphere synchronous activity is presented. Various conjectures on how meaning arises and how reasoning and problem solving is done are presented. These in...