Scalable Methods for Encoding and Comparing Patterns in Commerci... | Collin Francel | RRS Live 2024 скачать в хорошем качестве

Scalable Methods for Encoding and Comparing Patterns in Commerci... | Collin Francel | RRS Live 2024

Collin Francel is a Sophomore Data Science major in the Randall Research Scholars Program (RRSP). Their research project presentation, "Scalable Methods for Encoding and Comparing Patterns in Commercial Sex Ads," was completed under the advisement of Dr. Nick Freeman from the Information Systems, Statistics, & Management Science Department. Project Description: Sex trafficking is a serious problem affecting an estimated 15,000 to 50,000 women and children in the United States. Many trafficking organizations post advertisements on escort websites. As such, it becomes possible to use data analysis techniques to detect patterns of trafficking organizations and provide their information to law enforcement. A sign of trafficking and grounds for further investigation is seen when many different posts and images can be linked together, implying that a coordinated organization is behind the posts. In this work, we re-examine existing techniques for linking text data between two posts together.