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Aasish Pappu
Researcher at Yahoo!
Publications - 48
Citations - 497
Aasish Pappu is an academic researcher from Yahoo!. The author has contributed to research in topics: Dialog box & Automatic summarization. The author has an hindex of 11, co-authored 48 publications receiving 401 citations. Previous affiliations of Aasish Pappu include Indian Institute of Information Technology, Allahabad & Carnegie Mellon University.
Papers
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Proceedings ArticleDOI
Lightweight Multilingual Entity Extraction and Linking
TL;DR: An accurate and lightweight, multilingual named entity recognition (NER) and linking (NEL) system that achieves state-of-the-art performance on TAC KBP 2013 multilingual data and on English AIDA CONLL data is presented.
Proceedings ArticleDOI
Finding Good Conversations Online: The Yahoo News Annotated Comments Corpus
TL;DR: This work presents a dataset and annotation scheme for the new task of identifying “good” conversations that occur online, which it is called ERICs: Engaging, Respectful, and/or Informative Conversations, which is one of the largest annotated corpora of online human dialogues, with the most detailed set of annotations.
Proceedings ArticleDOI
100, 000 Podcasts: A Spoken English Document Corpus.
Ann Clifton,Sravana Reddy,Yongze Yu,Aasish Pappu,Rezvaneh Rezapour,Hamed Bonab,Maria Eskevich,Gareth J. F. Jones,Jussi Karlgren,Ben Carterette,Rosie Jones +10 more
TL;DR: The Spotify Podcast Dataset is introduced, a new corpus of 100,000 podcasts that is orders of magnitude larger than previous speech corpora used for search and summarization and opens up new avenues for research.
Proceedings Article
Automatically Identifying Good Conversations Online (Yes, They Do Exist!).
TL;DR: A new task is defined of identifying “good” conversations, which are called ERICs—Engaging, Respectful, and/or Informative Conversations, posted in response to online news articles and in debate forums.
Proceedings Article
Humor in Collective Discourse: Unsupervised Funniness Detection in the New Yorker Cartoon Caption Contest
Dragomir R. Radev,Amanda Stent,Joel Tetreault,Aasish Pappu,Aikaterini Iliakopoulou,Agustin Chanfreau,Paloma de Juan,Jordi Vallmitjana,Alejandro Jaimes,Rahul Jha,Bob Mankoff +10 more
TL;DR: It is shown that negative sentiment, human-centeredness, and lexical centrality most strongly match the funniest captions, followed by positive sentiment.