Papers by Elaheh ShafieiBavani
Summarization Evaluation in the Absence of Human Model Summaries Using the Compositionality of Word Embeddings (C18-1)
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| Challenge: | Existing summary evaluation methods rely on multiple model summaries to evaluate quality of summary outputs. |
| Approach: | They propose a new summary evaluation approach that does not require human model summaries . they exploit compositional capabilities of word embeddings to develop features . |
| Outcome: | The proposed metric replicates human-generated summarization scores on data from TAC 2008 and 2009 . the features are then used to train a learning model for predicting the summary content quality in the absence of gold models. |
A Graph-theoretic Summary Evaluation for ROUGE (D18-1)
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| Challenge: | ROUGE is one of the most widely used evaluation metrics for text summarization. |
| Approach: | They propose to use ROUGE to evaluate summaries based on lexical and semantic similarities. |
| Outcome: | The proposed method improves ROUGE's correlation with human judgments by exploiting lexical and semantic similarities. |