• Publications
  • Influence
Extracting user profiles from large scale data
TLDR
This work first describes an efficient user profiling framework with high user profiling quality guarantees, then describes a scalable implementation of the proposed framework in Apache Hadoop and discusses its challenges. Expand
TalkSumm: A Dataset and Scalable Annotation Method for Scientific Paper Summarization Based on Conference Talks
TLDR
This paper proposes a novel method that automatically generates summaries for scientific papers, by utilizing videos of talks at scientific conferences, and hypothesizes that such talks constitute a coherent and concise description of the papers’ content, and can form the basis for good summaries. Expand
Neural Response Generation for Customer Service based on Personality Traits
TLDR
A neural response generation model that generates responses conditioned on a target personality that achieves performance improvements in both perplexity and BLEU scores over a baseline sequence-to-sequence model, and is validated by human judges. Expand
Classifying Emotions in Customer Support Dialogues in Social Media
TLDR
It is shown that, in addition to text based turn features, dialogue features can significantly improve detection of emotions in social media customer service dialogues and help predict emotional techniques used by customer service agents. Expand
Best-Effort Top-k Query Processing Under Budgetary Constraints
TLDR
Novel algorithms for budget-aware top-k processing that produce results that have a significantly higher quality than those of state-of-the-art budget-oblivious solutions are introduced. Expand
Emotion Detection from Text via Ensemble Classification Using Word Embeddings
TLDR
This work proposes a new approach that utilizes pre-trained, dense word embedding representations and introduces an ensemble approach combining both sparse and dense representations. Expand
Detecting Egregious Conversations between Customers and Virtual Agents
TLDR
This paper outlines an approach to detecting bad conversations, using behavioral cues from the user, patterns in agent responses, and user-agent interaction, and shows that using these features improves the detection F1-score by around 20% over using textual features alone. Expand
Overview of the First Workshop on Scholarly Document Processing (SDP)
TLDR
The 1st Workshop on Scholarly Document Processing at EMNLP 2020 as a virtual event, aimed at reaching to the broader NLP and AI/ML community, pool distributed efforts and enable shared access to published research. Expand
Overview and Insights from the Shared Tasks at Scholarly Document Processing 2020: CL-SciSumm, LaySumm and LongSumm
TLDR
The quality and quantity of the submissions show that there is ample interest in scholarly document summarization, and the state of the art in this domain is at a midway point between being an impossible task and one that is fully resolved. Expand
A fusion approach to cluster labeling
TLDR
It is demonstrated that, overall, the cluster labeling fusion methods that further consider the labeler's decisiveness provide the best labeling performance. Expand
...
1
2
3
4
...