A Comparative Study of Information-Gathering Approaches for Answering Help-Desk Email Inquiries

Abstract. We present a comparative study of corpus-based methods for the automatic synthesis of email responses to help-desk requests. Our methods were developed by considering two operational dimensions: (1) information-gathering technique, and (2) granularity of the information. In particular, we investigate two techniques – retrieval and prediction – applied to information represented at two levels of granularity – sentence level and document level. We also developed a hybrid method that combines prediction with retrieval. Our results show that the different approaches are applicable in different situations, addressing a combined 72 % of the requests with either complete or partial responses.

Findings of the 2012 Workshop on Statistical Machine Translation

This paper presents the results of the WMT12 shared tasks, which included a translation task, a task for machine translation evaluation metrics, and a task for run-time estimation of machine translation quality. We conducted a large-scale manual evaluation of 103 machine translation systems submitted by 34 teams. We used the ranking of these systems to measure how strongly automatic metrics correlate with human judgments of translation quality for 12 evaluation metrics. We introduced a new quality estimation task this year, and evaluated submissions from 11 teams