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arXiv 2211.04417cs.CL
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nBIIG: A Neural BI Insights Generation System for Table Reporting

IBM Research(IBM研究院)

Yotam Perlitz, Dafna Sheinwald, Noam Slonim, Michal Shmueli-Scheuer

英文摘要:

We present nBIIG, a neural Business Intelligence (BI) Insights Generation system. Given a table, our system applies various analyses to create corresponding RDF representations, and then uses a neural model to generate fluent textual insights out of these representations. The generated insights can be used by an analyst, via a human-in-the-loop paradigm, to enhance the task of creating compelling table reports. The underlying generative neural model is trained over large and carefully distilled data, curated from multiple BI domains. Thus, the system can generate faithful and fluent insights over open-domain tables, making it practical and useful.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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