Now showing items 21-40 of 741

    • 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 ...
    • NECE: Narrative Event Chain Extraction Toolkit 

      Xu, Guangxuan; Toro Isaza, Paulina; Li, Moshi; Oloko, Akintoye; Yao, Bingsheng; Sanctos, Cassia; Adebiyi, Aminat; Hou, Yufang; Peng, Nanyun; Wang, Dakuo (arXiv, 2022-07-17)
      To understand a narrative, it is essential to comprehend its main characters and the associated major events; however, this can be challenging with lengthy and unstructured narrative texts. To address this, we introduce ...
    • 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. ...
    • 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 ...
    • DeFi Survival Analysis: Insights into Risks and User Behavior 

      Green, Aaron; Cammilleri, Christopher; Erickson, John S.; Seneviratne, Oshani; Bennett, Kristin P. (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 ...
    • 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, ...
    • StoryBuddy: A Human-AI Collaborative Chatbot for Parent-Child Interactive Storytelling with Flexible Parental Involvement 

      Zhang, Zheng; Xu, Ying; Wang, Yanhao; Yao, Bingsheng; Ritchie, Daniel; Wu, Tongshuang; Yu, Mo; Wang, Dakuo; Jia-Jun Li, Toby (ACM, 2022-04-29)
      Despite its benefits for children’s skill development and parent-child bonding, many parents do not often engage in interactive storytelling by having story-related dialogues with their child due to limited availability ...
    • 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) ...
    • End-to-End Table Question Answering via Retrieval-Augmented Generation 

      Pan, FeiFei; Canim, Mustafa; Glass, Michael; Gliozzo, Alfio; Hendler, James A. (arXiv, 2022-03)
      Most existing end-to-end Table Question Answering (Table QA) models consist of a two-stage framework with a retriever to select relevant table candidates from a corpus and a reader to locate the correct answers from table ...
    • InDO: the Institute Demographic Ontology 

      Keshan, Neha; Fontaine, Kathy; Hendler, James A. (Springer, Cham, 2022-01-01)
      Graduate education institutes in the United States (US) have been working on programs to increase the number of students and faculty from marginalized communities. When choosing to pursue a doctoral degree, the common ...
    • Incentivized Research Data Sharing, Reusing, and Repurposing with Blockchain Technologies 

      Seneviratne, Oshani; McGuinness, Deborah L. (University of Hawaii at Manoa, 2022)
      Data sharing is very important for accelerating scientific research, business innovations, and for informing individuals. Yet, concerns over data privacy, cost, and lack of secure data-sharing solutions have prevented data ...
    • A Mathematics Pipeline to Student Success in Data Analytics through Course-Based Undergraduate Research 

      Bennett, Kristin P.; Erickson, John S.; Svirsky, Amy; Seddon, Josephine (The Mathematics Enthusiast, 2021-12-16)
      This paper reports on Data Analytics Research (DAR), a course-based undergraduate research experience (CURE) in which undergraduate students conduct data analysis research on open real- world problems for industry, university, ...
    • Developing the Cross-Disciplinary Information Model for NASA’s Science Mission Directorate 

      Duerr, Ruth; Eleish, Ahmed; Parsons, Mark; Berrios, Daniel; Bugbee, Kaylin; Fox, Peter (AGU, 2021-12)
      The five divisions of NASAs Science Mission Directorate (SMD) represent a very broad spectrum of academic disciplines, ranging from Astronomy, to Planetary science, to Heliophysics, Earth science, Biology and Physical ...