Benchmark for Complex Answer Retrieval
Federico Nanni, Bhaskar Mitra, Matt Magnusson, Laura Dietz · 2017
Providing answers to complex information needs is a challenging task. The new TREC Complex Answer Retrieval (TREC CAR) track introduces a large-scale dataset where paragraphs are to be retrieved in response to outlines of Wikipedia articles representing complex information needs. We present early results from a variety of approaches -- from standard information retrieval methods (e.g., TF-IDF) to complex systems that adopt query expansion, knowledge bases and deep neural networks. The goal is to offer an overview of some promising approaches to tackle this problem.