Now showing items 1-20 of 635

    • Analyzing and predicting success of professional musicians 

      Kang, Inwon; Michael, Mandulak; Szymanśki, Bolesław (Scientific Reports, 2022-12-17)
      The emergence of streaming services, e.g., Spotify, has changed the way people listen to music and the way professional musicians achieve fame and success. Classical music has been the backbone of Western media for a long ...
    • Semantic Technologies for Clinically Relevant Personal Health Applications 

      Chen, Ching-Hau; Gruen, Daniel; Harris, Jonathan; Hendler, James A.; McGuinness, Deborah L.; Monti, Marco; Rastogi, Nidhi; Seneviratne, Oshani; Zaki, Mohammed J (Springer, 2022-11-23)
      Despite recent advances in digital health solutions and machine learning, personal health applications that aim to modify health behaviors are still limited in their ability to offer more personalized decision support. ...
    • Guiding principles for technical infrastructure to support computable biomedical knowledge 

      McCusker, Jamie; McIntosh, Leslie D.; Shaffer, Chris; Boisvert, Peter; Ryan, James; Navale, Vivek; Topaloglu, Umit; Richesson, Rachel L. (Wiley Periodicals LLC, 2022-11-01)
      Over the past 4 years, the authors have participated as members of the Mobilizing Computable Biomedical Knowledge Technical Infrastructure working group and focused on conceptualizing the infrastructure required to use ...
    • Building and Analyzing the Brazilian Legal Knowledge Graph 

      Pires, Rilder S.; Santos, Henrique; Guedes, Ricardo; Neto, João A. Monteiro; Caminha, Carlos; Furtado, Vasco (Joint Proceedings of the 3th International Workshop on Artificial Intelligence Technologies for Legal Documents (AI4LEGAL 2022) and the 1st International Workshop on Knowledge Graph Summarization (KGSum 2022), 2022-11-01)
      Artificial Intelligence has proven to be effective in streamlining processes in several domains. The Brazilian judiciary, specifically, has a very large number of cases, above the work capacity of the courts, generating ...
    • EaT-PIM: Substituting Entities in Procedural Instructions Using Flow Graphs and Embeddings 

      Shirai, Sola; Kim, HyeongSik (Springer, Cham, 2022-10-16)
      When cooking, it can sometimes be desirable to substitute ingredients for purposes such as avoiding allergens, replacing a missing ingredient, or exploring new flavors. More generally, the problem of substituting entities ...
    • Crowdsourcing Perceptions of Gerrymandering 

      Kelly, Benjamin; Kang, Inwon; Xia, Lirong (Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 2022-10-14)
      Gerrymandering is the manipulation of redistricting to influence the results of a set of elections for local representatives. Gerrymandering has the potential to drastically swing power in legislative bodies even with no ...
    • Semi automated process for generating knowledge graphs for marginalized community doctoral-recipients. 

      Keshan, Neha; Fontaine, Kathy; Hendler, James A. (Emerald Publishing Limited, 2022-10-13)
      Purpose – This paper aims to describe the “InDO: Institute Demographic Ontology” and demonstrates the InDO-based semiautomated process for both generating and extending a knowledge graph to provide a comprehensive resource ...
    • Knowledge Graph Construction from Data, Data Dictionaries, and Codebooks: the National Health and Nutrition Examination Surveys Use Case 

      Santos, Henrique; Pinheiro, Paulo; McGuinness, Deborah L. (2022-09-29)
      CDC’s National Health and Nutrition Examination Surveys (NHANES) is a continuous survey that aims to study the relationship between diet, nutrition, and health and their roles in designated population subgroups with selected ...
    • Differences in Cancer Phenotypes Among Frequent CHEK2 Variants and Implications for Clinical Care—Checking CHEK2 

      Bychkovsky, Brittany L; Agaoglu, Nihat B; Horton, Carolyn; Zhou, Jing; Yussuf, Amal; Hemyari, Parichehr; Richardson, Marcy E; Young, Colin; LaDuca, Holly; McGuinness, Deborah L.; Scheib, Rochelle; Garber, Judy E; Rana, Huma Q (JAMA Oncol., 2022-09-22)
      Importance Germline CHEK2 pathogenic variants (PVs) are frequently detected by multigene cancer panel testing (MGPT), but our understanding of PVs beyond c.1100del has been limited. Objective To compare cancer phenotypes ...
    • The (Uncomputable!) Meaning of Ethically Charged Natural Language, for Robots, and Us, from Hypergraphical Inferential Semantics 

      Bringsjord, Selmer; Hendler, James A.; Govindarajulu, Naveen Sundar; Ghosh, Rikhiya; Giancola, Michael (Springer, Cham, 2022-09-08)
      The year is 2030. A two-young-child, two-parent household, the Rubensteins, owns and employs a state-of-the-art household robot, Rodney. With the parents out, the children ask Rodney to perform some action �� that violates ...
    • Should we tweet this? Generative response modeling for predicting reception of public health messaging on Twitter 

      Sanders, Abraham; Ray-Majumder, Debjani; Erickson, John S.; Bennett, Kristin P. (Association for Computing Machinery, New York, NY, USA, 2022-07-01)
      The way people respond to messaging from public health organizations on social media can provide insight into public perceptions on critical health issues, especially during a global crisis such as COVID-19. It could be ...
    • An Ontology for Fairness Metrics 

      Franklin, Jade S; Bhanot, Karan; Ghalwash, Mohamed; Bennett, Kristin P.; McCusker, Jamie; McGuinness, Deborah L. (ACM, 2022-07)
      Recent research has revealed that many machine-learning models and the datasets they are trained on suffer from various forms of bias, and a large number of different fairness metrics have been created to measure this bias. ...
    • DeFi Survival Analysis: Insights into Risks and User Behavior 

      Green, Aaron; Cammilleri, Christopher; Erickson, John S.; Seneviratne, Oshani; Bennett, Kristin (Springer, 2022-06)
      We propose a decentralized finance (DeFi) survival analysis approach for discovering and characterizing user behavior and risks in lending protocols. We demonstrate how to gather and prepare DeFi transaction data for ...
    • Loaded Language and Conspiracy Theorizing 

      Klein, Emily; Hendler, James A. (UC Merced, 2022-06)
      Loaded language is an umbrella term for words, phrases, and overall rhetorical strategies that have strong emotional implications and intent to sway others. Belief in conspiracy theories is tied to a range of strong emotions ...
    • FAIR and Interactive Data Graphics from a Scientific Knowledge Graph 

      Deagen, Michael E.; McCusker, Jamie; Fateye, Tolulomo; Stouffer, Samuel; Brinson, L. Cate; McGuinness, Deborah L.; Schadler, Linda S. (Nature Scientific Data, 2022-05)
      Graph databases capture richly linked domain knowledge by integrating heterogeneous data and metadata into a unified representation. Here, we present the use of bespoke, interactive data graphics (bar charts, scatter plots, ...
    • Designing a strong test for measuring true common-sense reasoning 

      Kejriwal, Mayank; Santos, Henrique; Mulvehill, Alice; McGuinness, Deborah L. (Nature Machine Intelligence, 2022-04-22)
      Common-sense reasoning has recently emerged as an important test for artificial general intelligence, especially given the much-publicized successes of language representation models such as T5, BERT and GPT-3. Currently, ...
    • Understanding Clinician Workflows to Design AI Risk Prediction Models 

      Zhang, O.; Chari, Shruthi; Saiz, F. S.; Gruen, Daniel; Acharya, P.; Seneviratne, Oshani; Meter, P.; McGuinness, Deborah L.; Chakraborty, P. (AMIA, 2022-04)
    • Knowledge graphs: Introduction, history, and perspectives 

      Chaudhri, V. K.; Baru, C.; Chittar, N.; Dong, X. L.; Genesereth, M.; Hendler, James A.; Kalyanpur, A.; Lenat, D.; Sequeda, Juan; Vrandečić, D.; Wang, K. (Wiley, 2022-03-31)
      Knowledge graphs (KGs) have emerged as a compelling abstraction for organizing the world's structured knowledge and for integrating information extracted from multiple data sources. They are also beginning to play a central ...
    • Auto-Transfer: Learning to Route Transferrable Representations 

      Murugesan, Keerthiram; Sadashivaiah, Vijay; Luss, Ronny; Shanmugam, Karthikeyan; Chen, Pin-Yu; Dhurandhar, Amit (International Conference on Learning Representations, 2022-03-15)
      Knowledge transfer between heterogeneous source and target networks and tasks has received a lot of attention in recent times as large amounts of quality labeled data can be difficult to obtain in many applications. Existing ...
    • A Theoretically Grounded Benchmark for Evaluating Machine Commonsense 

      Santos, Henrique; Shen, Ke; Mulvehill, Alice M.; Razeghi, Yasaman; McGuinness, Deborah L.; Kejriwal, Mayank (arXiv, 2022-03)
      Programming machines with commonsense reasoning (CSR) abilities is a longstanding challenge in the Artificial Intelligence community. Current CSR benchmarks use multiple-choice (and in relatively fewer cases, generative) ...