Papers by Behzad Golshan

3 papers
Essentia: Mining Domain-specific Paraphrases with Word-Alignment Graphs (D19-53)

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Challenge: Existing methods for mining general-purpose paraphrases are often based on statistical methods, but domain-specific corpora are too small to fit statistical methods.
Approach: They propose a method to mine paraphrases from a small set of sentences that roughly share the same topic or intent.
Outcome: The proposed method obtains high quality paraphrases as evaluated by crowd workers.
SubjQA: A Dataset for Subjectivity and Review Comprehension (2020.emnlp-main)

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Challenge: Subjectivity is the expression of internal opinions or beliefs which cannot be objectively observed or verified.
Approach: They develop a dataset which investigates subjectivity in question answering . they find that subjectivity is an important feature in the case of QA .
Outcome: The proposed dataset shows that subjectivity is an important feature in question answering (QA) it also shows that subjective questions and answers can have more complex interactions than previously thought.
HappyDB: A Corpus of 100,000 Crowdsourced Happy Moments (L18-1)

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Challenge: Recent research has focused on developing technologies that help users incorporate the findings of the science of happiness into their daily lives.
Approach: They crowd-sourced HappyDB, a corpus of 100,000 happy moments, and applied several state-of-the-art analysis techniques to analyze HappyDB.
Outcome: The proposed technology can understand how people express their happy moments in text and analyze them using state-of-the-art techniques.

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