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Semantic Message Passing for Generating Linked Data from Tables
This work presents implementation details of a joint inference module that uses knowledge from the linked open data (LOD) cloud to jointly infer the semantics of column headers, table cell values and relations between columns. Expand
CyberTwitter: Using Twitter to generate alerts for cybersecurity threats and vulnerabilities
CyberTwitter, a system to discover and analyze cybersecurity intelligence on Twitter and serve as a OSINT (Open-source intelligence) source is described, which uses the Semantic Web RDF to represent the intelligence gathered and SWRL rules to reason over extracted intelligence to issue alerts for security analysts. Expand
Using Linked Data to Interpret Tables
An approach that uses linked data to interpret such tables and associate their components with nodes in a reference linked data collection, which assigns a class to table columns, links table cells to entities, and inferred relations between columns to properties is described. Expand
Exploiting a Web of Semantic Data for Interpreting Tables
Much of the world’s knowledge is contained in structured documents like spreadsheets, database relations and tables in documents found on the Web and in print. The information in these tables mightExpand
Extracting Information about Security Vulnerabilities from Web Text
The results suggest that the initial work on developing a framework to detect and extract information about vulnerabilities and attacks from Web text can be useful in monitoring streams of text from social media or chat rooms to identify potential new attacks and vulnerabilities or to collect data on the spread and volume of existing ones. Expand
Automatically Generating Government Linked Data from Tables
This work represents a table’s meaning by mapping columns to classes in an appropriate ontology, linking cell values to literal constants, implied measurements, or entities in the linked data cloud and discovering or and identifying relations between columns. Expand
A Domain Independent Framework for Extracting Linked Semantic Data from Tables
A domain independent framework for interpreting the intended meaning of tables and representing it as Linked Data is described, using techniques grounded in graphical models and probabilistic reasoning to infer meaning associated with a table. Expand
T2LD: Interpreting and Representing Tables as Linked Data
We describe a framework and prototype system for interpreting tables and extracting entities and relations from them, and producing a linked data representation of the table's contents. This can beExpand
Integrated access to big data polystores through a knowledge-driven framework
This paper presents the Semantics Toolkit (SemTK), a framework that enables access to polyglot-persistent Big Data stores while giving the appearance that all data is fully captured within a knowledge graph. Expand
TABEL -- A Domain Independent and Extensible Framework for Inferring the Semantics of Tables
This dissertation presents TABEL - a domain independent & extensible framework to infer the semantics of tables and represent them as RDF Linked Data, and builds a proof of concept user interactive system which utilizes the inferred semantics to help researchers discover, extract and integrate data from relevant studies to produce meta-analysis reports. Expand