Summary of Auto Faq Generation, by Anjaneya Teja Kalvakolanu et al.
Auto FAQ Generation
by Anjaneya Teja Kalvakolanu, NagaSai Chandra, Michael Fekadu
First submitted to arxiv on: 13 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed system generates FAQ documents by extracting salient sentences from text documents as proxy answers to aggregated reader questions. The method utilizes existing text summarization, sentence ranking via TextRank algorithm, and question-generation tools. The initial set of questions and answers is then filtered using heuristics to remove invalid queries. Human evaluation assesses the generated questions on grammar, meaningfulness, and answerability within summarized context. Participants found 71% of questions meaningful. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A team developed a system to create FAQ documents by extracting important sentences from big texts. These sentences are like answers to many people’s questions. They used special tools to get these sentences and then filtered out the bad ones. People checked the generated questions and said most of them were good and made sense. |
Keywords
» Artificial intelligence » Summarization
