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researcher

William W. Cohen

Google

79 papers hereh-index 9351.8k citations435 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author3
  • first author7
  • middle author26
  • last author40

Across the 76 of 79 papers where every author was matched, so the position is known.

fields
  • cs.CL45
  • cs.LG15
  • cs.AI12
  • cs.IR4
  • cs.CV2
  • q-bio.MN1
affiliations
  • Google
Homepage
same name
  • William W. Cohen — 6 papers, h 3
  • William W. Cohen — 3 papers, h 2
  • William W. Cohen — 1 paper
  • William W. Cohen — 1 paper, h 3
  • William W. Cohen — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
19952023
most citedTransNets: Learning to Transform for Recommendation

291 citations · 3k across the 73 of their papers we have counts for

collaborators
Showing cs.IRShow all

4 papers · 1 filter

cs.IR2019

A Road-map Towards Explainable Question Answering A Solution for Information Pollution

Saeedeh Shekarpour, Faisal Alshargi

The increasing rate of information pollution on the Web requires novel solutions to tackle that. Question Answering (QA) interfaces are simplified and user-friendly interfaces to a…

cs.IR2017★ 26 cited

Explainable Entity-based Recommendations with Knowledge Graphs

Rose Catherine, Kathryn Mazaitis, Maxine Eskenazi +1

Explainable recommendation is an important task. Many methods have been proposed which generate explanations from the content and reviews written for items. When review text is una…

cs.IR2017★ 291 cited

TransNets: Learning to Transform for Recommendation

Rose Catherine, William Cohen

Recently, deep learning methods have been shown to improve the performance of recommender systems over traditional methods, especially when review text is available. For example, a…

cs.IR2016★ 7 cited

Semantic Scan: Detecting Subtle, Spatially Localized Events in Text Streams

Abhinav Maurya, Kenton Murray, Yandong Liu +3

Early detection and precise characterization of emerging topics in text streams can be highly useful in applications such as timely and targeted public health interventions and dis…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.