Semantic Scholar Open Access 2022 6 sitasi

TARexp: A Python Framework for Technology-Assisted Review Experiments

Eugene Yang D. Lewis

Abstrak

Technology-assisted review (TAR) is an important industrial application of information retrieval (IR) and machine learning (ML). While a small TAR research community exists, the complexity of TAR software and workflows is a major barrier to entry. Drawing on past open source TAR efforts, as well as design patterns from the IR and ML open source software, we present an open source Python framework for conducting experiments on TAR algorithms. Key characteristics of this framework are declarative representations of workflows and experiment plans, the ability for components to play variable numbers of workflow roles, and state maintenance and restart capabilities. Users can draw on reference implementations of standard TAR algorithms while incorporating novel components to explore their research interests. The framework is available at https://github.com/eugene-yang/tarexp.

Topik & Kata Kunci

Penulis (2)

E

Eugene Yang

D

D. Lewis

Format Sitasi

Yang, E., Lewis, D. (2022). TARexp: A Python Framework for Technology-Assisted Review Experiments. https://doi.org/10.1145/3477495.3531663

Akses Cepat

Lihat di Sumber doi.org/10.1145/3477495.3531663
Informasi Jurnal
Tahun Terbit
2022
Bahasa
en
Total Sitasi
Sumber Database
Semantic Scholar
DOI
10.1145/3477495.3531663
Akses
Open Access ✓