Search Results for author: Behzad Golshan

Found 9 papers, 4 papers with code

Adaptive Rule Discovery for Labeling Text Data

no code implementations13 May 2020 Sainyam Galhotra, Behzad Golshan, Wang-Chiew Tan

At the same time, creating a labeled subset of the data can be costly and even infeasible in imbalanced settings.

SubjQA: A Dataset for Subjectivity and Review Comprehension

1 code implementation EMNLP 2020 Johannes Bjerva, Nikita Bhutani, Behzad Golshan, Wang-Chiew Tan, Isabelle Augenstein

We find that subjectivity is also an important feature in the case of QA, albeit with more intricate interactions between subjectivity and QA performance.

Question Answering Sentiment Analysis +1

Enhancing Review Comprehension with Domain-Specific Commonsense

no code implementations6 Apr 2020 Aaron Traylor, Chen Chen, Behzad Golshan, Xiaolan Wang, Yuliang Li, Yoshihiko Suhara, Jinfeng Li, Cagatay Demiralp, Wang-Chiew Tan

In this paper, we introduce xSense, an effective system for review comprehension using domain-specific commonsense knowledge bases (xSense KBs).

Aspect Extraction Knowledge Distillation +2

Sampo: Unsupervised Knowledge Base Construction for Opinions and Implications

1 code implementation AKBC 2020 Nikita Bhutani, Aaron Traylor, Chen Chen, Xiaolan Wang, Behzad Golshan, Wang-Chiew Tan

Since it can be expensive to obtain training data to learn to extract implications for each new domain of reviews, we propose an unsupervised KBC system, Sampo, Specifically, Sampo is tailored to build KBs for domains where many reviews on the same domain are available.

Scalable Semantic Querying of Text

no code implementations3 May 2018 Xiaolan Wang, Aaron Feng, Behzad Golshan, Alon Halevy, George Mihaila, Hidekazu Oiwa, Wang-Chiew Tan

KOKO is novel in that its extraction language simultaneously supports conditions on the surface of the text and on the structure of the dependency parse tree of sentences, thereby allowing for more refined extractions.

HappyDB: A Corpus of 100,000 Crowdsourced Happy Moments

2 code implementations LREC 2018 Akari Asai, Sara Evensen, Behzad Golshan, Alon Halevy, Vivian Li, Andrei Lopatenko, Daniela Stepanov, Yoshihiko Suhara, Wang-Chiew Tan, Yinzhan Xu

The science of happiness is an area of positive psychology concerned with understanding what behaviors make people happy in a sustainable fashion.

Art Analysis

What do row and column marginals reveal about your dataset?

no code implementations NeurIPS 2013 Behzad Golshan, John Byers, Evimaria Terzi

Numerous datasets ranging from group memberships within social networks to purchase histories on e-commerce sites are represented by binary matrices.

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