30 citations · 233 across the 58 of their papers we have counts for
6 papers · 1 filter
FlagIt: A System for Minimally Supervised Human Trafficking Indicator Mining
Mayank Kejriwal, Jiayuan Ding, Runqi Shao +2
In this paper, we describe and study the indicator mining problem in the online sex advertising domain. We present an in-development system, FlagIt (Flexible and adaptive generatio…
Always Lurking: Understanding and Mitigating Bias in Online Human Trafficking Detection
Kyle Hundman, Thamme Gowda, Mayank Kejriwal +1
Web-based human trafficking activity has increased in recent years but it remains sparsely dispersed among escort advertisements and difficult to identify due to its often-latent n…
Predicting Role Relevance with Minimal Domain Expertise in a Financial Domain
Mayank Kejriwal
Word embeddings have made enormous inroads in recent years in a wide variety of text mining applications. In this paper, we explore a word embedding-based architecture for predicti…
Using Contexts and Constraints for Improved Geotagging of Human Trafficking Webpages
Rahul Kapoor, Mayank Kejriwal, Pedro Szekely
Extracting geographical tags from webpages is a well-motivated application in many domains. In illicit domains with unusual language models, like human trafficking, extracting geot…
Supervised Typing of Big Graphs using Semantic Embeddings
Mayank Kejriwal, Pedro Szekely
We propose a supervised algorithm for generating type embeddings in the same semantic vector space as a given set of entity embeddings. The algorithm is agnostic to the derivation…
Information Extraction in Illicit Domains
Mayank Kejriwal, Pedro Szekely
Extracting useful entities and attribute values from illicit domains such as human trafficking is a challenging problem with the potential for widespread social impact. Such domain…