H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 65 Citations 25,677 226 World Ranking 1121 National Ranking 656

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Machine learning

The scientist’s investigation covers issues in Artificial intelligence, Machine learning, Social media, Artificial neural network and Mathematical optimization. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Pattern recognition, Generalized linear model, Information retrieval and Natural language processing. The various areas that Lyle H. Ungar examines in his Machine learning study include Task and Natural language.

His Social media study combines topics in areas such as Cognitive psychology, Well-being, Psychiatry, Disengagement theory and Mental illness. His research integrates issues of Network model, Extrapolation and Nonlinear system in his study of Artificial neural network. His Mathematical optimization research integrates issues from Bidding, Combinatorial auction, Estimation theory and Auction algorithm.

His most cited work include:

  • System for generation of user profiles for a system for customized electronic identification of desirable objects (2433 citations)
  • System and method for scheduling broadcast of and access to video programs and other data using customer profiles (1482 citations)
  • Methods and metrics for cold-start recommendations (1376 citations)

What are the main themes of his work throughout his whole career to date?

Lyle H. Ungar focuses on Artificial intelligence, Social media, Machine learning, Natural language processing and Data mining. His Artificial intelligence research incorporates elements of Task and Pattern recognition. His Social media study incorporates themes from Public health, Cognitive psychology and Social psychology, Personality.

Big Five personality traits is the focus of his Personality research. Lyle H. Ungar works in the field of Natural language processing, focusing on Sentence in particular.

He most often published in these fields:

  • Artificial intelligence (28.25%)
  • Social media (20.27%)
  • Machine learning (11.85%)

What were the highlights of his more recent work (between 2017-2021)?

  • Social media (20.27%)
  • Artificial intelligence (28.25%)
  • Natural language processing (10.48%)

In recent papers he was focusing on the following fields of study:

His scientific interests lie mostly in Social media, Artificial intelligence, Natural language processing, Task and Social psychology. His work carried out in the field of Social media brings together such families of science as Health care, Anxiety, Public health, Personality and Mental health. He usually deals with Artificial intelligence and limits it to topics linked to Machine learning and Quality and Regression.

His Natural language processing research incorporates themes from Context based, Word and Adverse drug reaction. Lyle H. Ungar has included themes like Range, Cognitive psychology and Cluster analysis in his Task study. When carried out as part of a general Social psychology research project, his work on Big Five personality traits and Set is frequently linked to work in Trait, therefore connecting diverse disciplines of study.

Between 2017 and 2021, his most popular works were:

  • Facebook language predicts depression in medical records. (141 citations)
  • Can Twitter be used to predict county excessive alcohol consumption rates (31 citations)
  • Estimating geographic subjective well-being from Twitter: A comparison of dictionary and data-driven language methods. (28 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Statistics
  • Machine learning

His primary areas of study are Social media, Artificial intelligence, Mental health, Social psychology and Natural language processing. His Social media research includes elements of Language model, Big Five personality traits, Personality, Data science and Depression. His Artificial intelligence study integrates concerns from other disciplines, such as Machine learning, Arabic, Core and State.

His Machine learning research includes themes of Task and Regression. His work is dedicated to discovering how Social psychology, Stress are connected with Adaptation and Control and other disciplines. While the research belongs to areas of Natural language processing, Lyle H. Ungar spends his time largely on the problem of Word, intersecting his research to questions surrounding Task and Debiasing.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

System and method for scheduling broadcast of and access to video programs and other data using customer profiles

Frederick Herz;Lyle Ungar;Jian Zhang;David Wachob.
(1995)

2703 Citations

Methods and metrics for cold-start recommendations

Andrew I. Schein;Alexandrin Popescul;Lyle H. Ungar;David M. Pennock.
international acm sigir conference on research and development in information retrieval (2002)

2184 Citations

Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach

H. Andrew Schwartz;Johannes C. Eichstaedt;Margaret L. Kern;Lukasz Dziurzynski.
PLOS ONE (2013)

1528 Citations

Efficient clustering of high-dimensional data sets with application to reference matching

Andrew McCallum;Kamal Nigam;Lyle H. Ungar.
knowledge discovery and data mining (2000)

1358 Citations

Clustering Methods for Collaborative Filtering

Lyle H. Ungar;Dean P. Foster.
national conference on artificial intelligence (1998)

1075 Citations

A hybrid neural network‐first principles approach to process modeling

Dimitris C. Psichogios;Lyle H. Ungar.
Aiche Journal (1992)

783 Citations

Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments

Alexandrin Popescul;Lyle H. Ungar;David M. Pennock;Steve Lawrence.
uncertainty in artificial intelligence (2001)

579 Citations

Automatic personality assessment through social media language.

Gregory Park;H. Andrew Schwartz;Johannes C. Eichstaedt;Margaret L. Kern.
Journal of Personality and Social Psychology (2015)

524 Citations

Iterative Combinatorial Auctions: Theory and Practice

David C. Parkes;Lyle H. Ungar.
national conference on artificial intelligence (2000)

498 Citations

Psychological Language on Twitter Predicts County-Level Heart Disease Mortality

Johannes C. Eichstaedt;Hansen Andrew Schwartz;Margaret L. Kern;Gregory Park.
Psychological Science (2015)

450 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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