Papers with manual adaptation
Hey Siri. Ok Google. Alexa: A topic modeling of user reviews for smart speakers (D19-55)
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| Challenge: | Using coherence scores to choose topics, we test whether the results help us to understand user interests and concerns. |
| Approach: | They analyze user reviews from Best Buy US website for smart speakers to determine whether they provide useful information for product analysis. |
| Outcome: | The proposed models capture brand performance and differences and differentiate the market into two distinct groups with different properties. |
Automatic Domain Adaptation Outperforms Manual Domain Adaptation for Predicting Financial Outcomes (P19-1)
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| Challenge: | In this paper, we automatically create sentiment dictionaries for predicting financial outcomes excess return and volatility. |
| Approach: | They propose to automatically adapt a domain-general dictionary to a financial domain and then manually adapt it to dictionaries for the finance domain. |
| Outcome: | The proposed dictionary outperforms the previous state of the art in predicting financial variables excess return and volatility. |
An Unsupervised Joint System for Text Generation from Knowledge Graphs and Semantic Parsing (2020.emnlp-main)
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| Challenge: | Knowledge graphs (KGs) vary greatly from one domain to another, resulting in a lack of domain-specific parallel graph-text data. |
| Approach: | They propose an unsupervised approach to graph-to-text generation and text-to graph knowledge extraction using WebNLG v2.1 and a new benchmark leveraging scene graphs from Visual Genome. |
| Outcome: | The proposed approach outperforms baselines on WebNLG v2.1 and a new benchmark leveraging scene graphs from Visual Genome. |