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Benchmark for Complex Answer Retrieval
2017
Proceedings of the ACM SIGIR International Conference on Theory of Information Retrieval - ICTIR '17
Providing answers to complex information needs is a challenging task. e 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. e goal is to o er
doi:10.1145/3121050.3121099
dblp:conf/ictir/NanniMMD17
fatcat:wtkbphutorcmvnhdz7mvtce6vq