Fake News Detection (FND) is an essential field in natural language processing that aims to identify and check the truthfulness of significant claims a news article decide veracity. FND finds its uses preventing social, political, national damage caused due misrepresentation facts may harm particular section society. Further, with explosive rise fake dissemination over social media, including i...

Existing models of diagnosis have not uni ed the notions of time, uncertainty and abduction which are necessary in domains such as clinical diagnosis, dynamic systems modeling, and fault diagnosis. We present a new approach which models information through linear constraints and nd that many aspects of our knowledge-base and inferencing mechanism are naturally suited towards these constraints. ...

This paper describes combined approaches of data preparation, neural network analysis, and fuzzy inferencing techniques (which we collectively call neuro-fuzzy engineering) to the problem of environmental modelling. The overall neuro-fuzzy architecture is presented, and specific issues associated with environmental modelling are discussed. A case study that shows how these techniques can be com...

In this paper, we describe a system that semantically annotates streams of reports about transnational criminal gangs in order to automatically produce models of the gangs’ membership and activities in the form of a semantic wiki. A gang ontology and semantic inferencing are used to annotate the reports and supplement entity and relationship annotations based on the local document context. Repo...

Prolog has been often used to represent the axioms and inference over RDF data models often by converting all the data to plain-text Prolog facts and programs. In this paper we present the PRODEF infrastructure for using Prolog for inferencing over RDF data on the Web by representing Prolog programs in RDF, allowing them to be distributed over the Web and even incomplete, and represent reasonin...

In this paper, we evoke first the ubiquity and the importance of the so-called ‘narrative’ information, showing that the usual ontological tools, both the ‘traditional’ and the ‘Semantic Web’ ones, are unable to offer complete and reliable solutions for representing and exploiting this type of information. We supply then some details about NKRL (Narrative Knowledge Representation Language), a k...

Many systems are partially stochastic in nature. We have derived datadriven approaches for extracting stochastic state machines (Markov models) directly from observed data. This chapter provides an overview of our approach with numerous practical applications. We have used this approach for inferring shipping patterns, exploiting computer system side-channel information, and detecting botnet ac...