Search Results for author: Tim Finin

Found 26 papers, 3 papers with code

A Practical Entity Linking System for Tables in Scientific Literature

no code implementations12 Jun 2023 Varish Mulwad, Tim Finin, Vijay S. Kumar, Jenny Weisenberg Williams, Sharad Dixit, Anupam Joshi

Entity linking is an important step towards constructing knowledge graphs that facilitate advanced question answering over scientific documents, including the retrieval of relevant information included in tables within these documents.

Entity Linking Knowledge Graphs +2

CAPD: A Context-Aware, Policy-Driven Framework for Secure and Resilient IoBT Operations

no code implementations2 Aug 2022 Sai Sree Laya Chukkapalli, Anupam Joshi, Tim Finin, Robert F. Erbacher

This ability to reason over the mission sensed environment and attack context permits the autonomous IoBT system to exhibit resilience in contested conditions.

Attribute Knowledge Graphs

Recognizing and Extracting Cybersecurtity-relevant Entities from Text

no code implementations2 Aug 2022 Casey Hanks, Michael Maiden, Priyanka Ranade, Tim Finin, Anupam Joshi

Cyber Threat Intelligence (CTI) is information describing threat vectors, vulnerabilities, and attacks and is often used as training data for AI-based cyber defense systems such as Cybersecurity Knowledge Graphs (CKG).

Entity Linking Knowledge Graphs +2

Generating Fake Cyber Threat Intelligence Using Transformer-Based Models

no code implementations8 Feb 2021 Priyanka Ranade, Aritran Piplai, Sudip Mittal, Anupam Joshi, Tim Finin

We evaluate with traditional approaches and conduct a human evaluation study with cybersecurity professionals and threat hunters.

Data Poisoning Knowledge Graphs +2

An Ensemble Approach for Compressive Sensing with Quantum

no code implementations8 Jun 2020 Ramin Ayanzadeh, Milton Halem, Tim Finin

We leverage the idea of a statistical ensemble to improve the quality of quantum annealing based binary compressive sensing.

Compressive Sensing

Improving Neural Named Entity Recognition with Gazetteers

1 code implementation6 Mar 2020 Chan Hee Song, Dawn Lawrie, Tim Finin, James Mayfield

The goal of this work is to improve the performance of a neural named entity recognition system by adding input features that indicate a word is part of a name included in a gazetteer.

named-entity-recognition Named Entity Recognition +1

Reinforcement Quantum Annealing: A Quantum-Assisted Learning Automata Approach

no code implementations1 Jan 2020 Ramin Ayanzadeh, Milton Halem, Tim Finin

We introduce the reinforcement quantum annealing (RQA) scheme in which an intelligent agent interacts with a quantum annealer that plays the stochastic environment role of learning automata and tries to iteratively find better Ising Hamiltonians for the given problem of interest.

Unfolding the Structure of a Document using Deep Learning

no code implementations29 Sep 2019 Muhammad Mahbubur Rahman, Tim Finin

Understanding and extracting of information from large documents, such as business opportunities, academic articles, medical documents and technical reports, poses challenges not present in short documents.

Cyber-All-Intel: An AI for Security related Threat Intelligence

no code implementations7 May 2019 Sudip Mittal, Anupam Joshi, Tim Finin

It uses multiple knowledge representations like, vector spaces and knowledge graphs in a 'VKG structure' to store incoming intelligence.

Knowledge Graphs

SURFACE: Semantically Rich Fact Validation with Explanations

no code implementations31 Oct 2018 Ankur Padia, Francis Ferraro, Tim Finin

Judging the veracity of a sentence making one or more claims is an important and challenging problem with many dimensions.

General Classification Sentence

Ontology-Grounded Topic Modeling for Climate Science Research

no code implementations28 Jul 2018 Jennifer Sleeman, Tim Finin, Milton Halem

In scientific disciplines where research findings have a strong impact on society, reducing the amount of time it takes to understand, synthesize and exploit the research is invaluable.

Understanding and representing the semantics of large structured documents

no code implementations24 Jul 2018 Muhammad Mahbubur Rahman, Tim Finin

Understanding large, structured documents like scholarly articles, requests for proposals or business reports is a complex and difficult task.

UMBC at SemEval-2018 Task 8: Understanding Text about Malware

no code implementations SEMEVAL 2018 Ankur Padia, Arpita Roy, Taneeya Satyapanich, Francis Ferraro, SHimei Pan, Youngja Park, Anupam Joshi, Tim Finin

We describe the systems developed by the UMBC team for 2018 SemEval Task 8, SecureNLP (Semantic Extraction from CybersecUrity REports using Natural Language Processing).


Understanding the Logical and Semantic Structure of Large Documents

no code implementations3 Sep 2017 Muhammad Mahbubur Rahman, Tim Finin

A key contribution of our research is modeling the logical and semantic structure of an electronic document.

BIG-bench Machine Learning Information Retrieval +3

Thinking, Fast and Slow: Combining Vector Spaces and Knowledge Graphs

no code implementations10 Aug 2017 Sudip Mittal, Anupam Joshi, Tim Finin

Knowledge graphs and vector space models are robust knowledge representation techniques with individual strengths and weaknesses.

Knowledge Graphs

Interactive Knowledge Base Population

no code implementations31 May 2015 Travis Wolfe, Mark Dredze, James Mayfield, Paul McNamee, Craig Harman, Tim Finin, Benjamin Van Durme

Most work on building knowledge bases has focused on collecting entities and facts from as large a collection of documents as possible.

Knowledge Base Population

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