Search Results for author: Arindam Pal

Found 11 papers, 1 papers with code

Legal Case Document Similarity: You Need Both Network and Text

1 code implementation26 Sep 2022 Paheli Bhattacharya, Kripabandhu Ghosh, Arindam Pal, Saptarshi Ghosh

Our experiments establish that our proposed network-based methods significantly improve the correlation with domain experts' opinion when compared to the existing methods for network-based legal document similarity.

Citation Recommendation Retrieval

Task Allocation using a Team of Robots

no code implementations20 Jul 2022 Haris Aziz, Arindam Pal, Ali Pourmiri, Fahimeh Ramezani, Brendan Sims

Task allocation using a team or coalition of robots is one of the most important problems in robotics, computer science, operational research, and artificial intelligence.

PhishSim: Aiding Phishing Website Detection with a Feature-Free Tool

no code implementations13 Jul 2022 Rizka Purwanto, Arindam Pal, Alan Blair, Sanjay Jha

This method examines the HTML of webpages and computes their similarity with known phishing websites, in order to classify them.

Incremental Learning Phishing Website Detection

Cascading Failures in Smart Grids under Random, Targeted and Adaptive Attacks

no code implementations25 Jun 2022 Sushmita Ruj, Arindam Pal

In this case, the degree, betweenness, or clustering coefficient is calculated before the start of each round, instead of at the beginning.

Clustering

Man versus Machine: AutoML and Human Experts' Role in Phishing Detection

no code implementations27 Aug 2021 Rizka Purwanto, Arindam Pal, Alan Blair, Sanjay Jha

Our paper compares the performances of six well-known, state-of-the-art AutoML frameworks on ten different phishing datasets to see whether AutoML-based models can outperform manually crafted machine learning models.

AutoML BIG-bench Machine Learning

PhishZip: A New Compression-based Algorithm for Detecting Phishing Websites

no code implementations22 Jul 2020 Rizka Purwanto, Arindam Pal, Alan Blair, Sanjay Jha

PhishZip outperforms the use of best-performing HTML-based features in past studies, with a true positive rate of 80. 04%.

BIG-bench Machine Learning

Hier-SPCNet: A Legal Statute Hierarchy-based Heterogeneous Network for Computing Legal Case Document Similarity

no code implementations7 Jul 2020 Paheli Bhattacharya, Kripabandhu Ghosh, Arindam Pal, Saptarshi Ghosh

We propose to augment the PCNet with the hierarchy of legal statutes, to form a heterogeneous network Hier-SPCNet, having citation links between case documents and statutes, as well as citation and hierarchy links among the statutes.

Methods for Computing Legal Document Similarity: A Comparative Study

no code implementations26 Apr 2020 Paheli Bhattacharya, Kripabandhu Ghosh, Arindam Pal, Saptarshi Ghosh

Computing similarity between two legal documents is an important and challenging task in the domain of Legal Information Retrieval.

Information Retrieval Retrieval

BB_Evac: Fast Location-Sensitive Behavior-Based Building Evacuation

no code implementations19 Feb 2020 Subhra Mazumdar, Arindam Pal, Francesco Parisi, V. S. Subrahmanian

Past work on evacuation planning assumes that evacuees will follow instructions -- however, there is ample evidence that this is not the case.

Scheduling Resources for Executing a Partial Set of Jobs

no code implementations10 Oct 2012 Venkatesan Chakaravarthy, Arindam Pal, Sambuddha Roy, Yogish Sabharwal

In this paper, we consider the problem of choosing a minimum cost set of resources for executing a specified set of jobs.

Data Structures and Algorithms

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