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Publications

Peer-reviewed papers, journal articles, books, and book chapters from the AICS group. Use the filter to search by author, title, or venue.

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Forthcoming

Mayank Kejriwal, Ke Shen.
A Lightweight Global Taxonomy Induction System for E-Commerce Concept Labels.
Lecture Notes in Social Networks, Springer Nature.

2026

Yidan Sun, Daiqi He, and Mayank Kejriwal.
Examining persistent inequities in financial complaint resolution for older Americans and veterans in the United States.
PNAS Nexus (Brief Reports) · Press: USC Information Sciences Institute.
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Zhisheng Tang, Ke Shen, and Mayank Kejriwal.
Evaluating estimative uncertainty in large language models.
NPJ Complexity · Press: The Conversation, Fortune, ISI Press.
Molly Miranker, Min-Hsueh Chiu, Mayank Kejriwal and Alberto Giordano.
Applying Knowledge Graphs: Migrant Decedent Case Trajectories in South Texas.
Journal of Forensic Sciences.

2025

Molly Miranker, Min-Hsueh Chiu, Mayank Kejriwal and Alberto Giordano.
Knowledge Graphing in Forensics: Modeling Forensic Case Trajectories Using News Media.
Journal of Forensic Sciences.
Navapat Nananukul and Mayank Kejriwal.
Semi-Automatic Extraction and Analysis of Health Equity Covariates in Registered Research Projects.
MDPI Applied Sciences.
Ke Shen and Mayank Kejriwal.
Defining and evaluating decision and composite risk in language models applied to natural language inference.
Engineering Applications of Artificial Intelligence (Elsevier).
Mayank Kejriwal.
Alcohol consumption among university students in ASEAN countries: a systematic review and meta-analysis.
Cambridge Prisms: Global Mental Health.
Yifang Zhu, Qiao Yu, Tristan Que, Lara Cushing, Gregory Pierce, Ke Shen, Mayank Kejriwal, and Yuan Yao.
Equity and reliability of public electric vehicle charging stations in the United States.
Nature Communications.
Navapat Nananukul and Mayank Kejriwal.
Medical School Ranking and Neighborhood Characteristics of Initial Practice Location Among PhysiciansMay..
Research Letter, JAMA Network Open.
Yidan Sun, Ke Shen, and Mayank Kejriwal.
Backlash or reinforcement? Donald Trump’s 2017 inauguration and shifting climate beliefs in the United States.
Nature Partner Journals, Climate Action.
Navapat Nananukul, Mayank Kejriwal.
HealthEQKG: A Knowledge Graph and Data Model for Health Equity Research.
ISWC Resource Track, 2025.
Mayank Kejriwal, Deborah L. McGuinness, and Henry Lieberman.
Commonsense AI in the History of the Web.
The ACM Web Conference (history track), 2025.
Cole Gawin, Yidan Sun, and Mayank Kejriwal.
Navigating Semantic Relations: Challenges for Language Models in Abstract Common-Sense Reasoning.
The ACM Web Conference, 2025 · Press: The Science Archive.

2024

Islam, Shafkat, Min-Hsueh Chiu, Trevor Bonjour, Ruy de Oliveira, Bharat Bhargava, and Mayank Kejriwal.
A Q-learning Novelty Search Strategy for Evaluating Robustness of Deep Reinforcement Learning in Open-world Environments.
IEEE Intelligent Systems.
Navapat Nananukul, Ke Shen and Mayank Kejriwal.
The plausibility machine commonsense (PMC) dataset: A massively crowdsourced human-annotated dataset for studying plausibility in large language models..
Data in Brief.
Nananukul, Navapat, Khanin Sisaengsuwanchai, and Mayank Kejriwal.
Cost-efficient prompt engineering for unsupervised entity resolution in the product matching domain.
Discover Artificial Intelligence.
Mayank Kejriwal, Henrique Santos, Ke Shen, Alice M. Mulvehill, Deborah McGuinness.
A noise audit of human-labeled benchmarks for machine commonsense reasoning.
Nature Scientific Reports · Press: The Conversation.
Yidan Sun and Mayank Kejriwal.
A Study of Firm-Switching of Inventors in Big Tech Using Public Patent Data.
Social Network Analysis and Mining Applications in Healthcare and Anomaly Detection · Publisher: Springer.
Cheng, Xiyao, Lakshmi Srinivas Edara, Yuanxun Zhang, Mayank Kejriwal, and Prasad Calyam.
Influence Role Recognition and LLM-Based Scholar Recommendation in Academic Social Networks.
IEEE 11th International Conference on Data Science and Advanced Analytics (DSAA).
Navapat Nananukul, Mayank Kejriwal.
Balancing Efficiency and Quality in LLM-Based Entity Resolution on Structured Data.
The IEEE/ACM ASONAM Conference, 2024, multi-disciplinary track.
Yongyi Ji, Zhisheng Tang and Mayank Kejriwal.
Is persona enough for personality? Using ChatGPT to reconstruct an agent's latent personality from simple descriptions.
ICML 2024 Workshop on Large Language Models and Cognition.
Mayank Kejriwal, Hamid Haidarian, Min-Hsueh Chiu, Andy Xiang, Deep Shrestha, and Faizan Javed.
A Semantic Search Engine for Helping Patients Find Doctors and Locations in a Large Healthcare Organization.
Proceedings of the 47th International ACM SIGIR Conference on · Research and Development in Information Retrieval (SIGIR ’24), held in Washington, DC, USA.
Navapat Nananukul, Mayank Kejriwal.
HALO: An Ontology for Representing Hallucinations in Generative Models.
Proceedings of the International Society for Optics and Photonics (SPIE) · National Harbor, Maryland, USA.
Calyam, Prasad, Mayank Kejriwal, Praveen Rao, Jianlin Cheng, Weichao Wang, Linquan Bai, et al..
Towards a Domain-Agnostic Knowledge Graph-as-a-Service Infrastructure for Active Cyber Defense with Intelligent Agents.
2023 IEEE Applied Imagery Pattern Recognition Workshop (AIPR).

2023

Ke Shen and Mayank Kejriwal.
Quantifying Confidence Shifts in a BERT-based Question Answering System Evaluated On Perturbed Instances.
PLOS One.
Henrique Santos, Alice M. Mulvehill, Ke Shen, Mayank Kejriwal, Deborah L. McGuinness.
TG-CSR: A human-labeled dataset grounded in nine formal commonsense categories.
Elsevier Data in Brief.
Henrique Santos, Ke Shen, Alice M. Mulvehill, Mayank Kejriwal, Deborah L. McGuinness.
A Theoretically Grounded Question Answering Data Set for Evaluating Machine Common Sense.
Data Intelligence, MIT Press.
Ke Shen, Mayank Kejriwal.
Quantifying COVID-19 policy impacts on subjective well-being during the early phase of the pandemic: A cross-sectional analysis of United States survey data from March to August 2020.
PLOS One.
Zhisheng Tang, Mayank Kejriwal.
Evaluating deep generative models on cognitive tasks: a case study.
Discover Artificial Intelligence.
Mayank Kejriwal, Akarsh Nagaraj.
Quantifying Gender Disparity in Pre-Modern English Literature using Natural Language Processing.
Journal of Data Science.
Ke Shen, Mayank Kejriwal.
Using conditional inference to quantify interaction effects of socio-demographic covariates of US COVID-19 vaccine hesitancy.
PLOS Global Public Health.
Zhisheng Tang, Mayank Kejriwal.
Can language representation models think in bets?.
Royal Society Open Science.
Ke Shen, Mayank Kejriwal.
An experimental study measuring the generalization of fine-tuned language representation models across commonsense reasoning benchmarks.
Expert Systems, Wiley.
Mayank Kejriwal.
Named Entity Resolution in Personal Knowledge Graphs.
Invited book chapter, Personal Knowledge Graphs: Methodology, tools and applications · Publisher: The Institution of Engineering and Technology · Editors: Sanju Tiwari, Francois Scharffe, Fernando Ortiz-Rodriguez, and Manas Gaur.
Multi-agent Game Domain: Monopoly.
Invited book chapter, A Unifying Framework for Formal Theories of Novelty · Publisher: Springer · Editors: Terrance Boult and Walter Scheirer.
Ke Shen, Mayank Kejriwal.
An Analytical Approximation of Simplicial Complex Distributions in Communication Networks.
The 12th International Conference on Complex Networks and their Applications.
Min-Hsueh Chiu, Mayank Kejriwal.
A Model and Structural Analysis of Networked Bitcoin Transaction Flows.
The 12th International Conference on Complex Networks and their Applications.
Yidan Sun, Mayank Kejriwal.
A structural study of Big Tech firm-switching of inventors in the post-recession era.
Foundations and Applications of Big Data Analytics (FAB), co-held with IEEE ASONAM · Press: USC/ISI research news.
Xinyu Liu, Tiancheng Sun, Diantian Fu, Zijue Li, Sheng Qian, Ruyue Meng, Mayank Kejriwal.
Automatic Semantic Typing of Pet E-Commerce Products Using Crowdsourced Reviews: An Experimental Study.
The Fifth Edition of the Knowledge Graph and Semantic Web Conference (KGSWC).
Prasad Calyam, Xiyao Cheng, Yuanxun Zhang, Harsh Joshi and Mayank Kejriwal.
Knowledge Graph-based Embedding for Connecting Scholars in Academic Social Networks.
The 10th IEEE International Data Science and Advanced Analytics (DSAA) Conference.
Ke Shen, Mayank Kejriwal.
Substructure Discovery in Commonsense Relations Using Graph Representation Learning.
The 2023 IntelliSys Conference, held in Amsterdam, The Netherlands.
Mayank Kejriwal.
Simulating and Quantifying Inequality in Strategic Agent Networks.
10th International Conference on Human Interaction & Emerging Technologies, held in Nice, France.
Mayank Kejriwal, Henrique Santos, Ke Shen, Alice M. Mulvehill and Deborah L. McGuinness.
Context-Rich Evaluation of Machine Common Sense.
Artificial General Intelligence (AGI) Conference, held in Stockholm, Sweden.
Zhisheng Tang, Mayank Kejriwal.
Can Language Models be used in Multistep Commonsense Planning Domains?.
Artificial General Intelligence (AGI) Conference, held in Stockholm, Sweden.

2022

Marina Haliem, Trevor Bonjour, Aala Alsalem, Shilpa Thomas, Hongyu Li, Vaneet Aggarwal,.
Decision Making in Monopoly using a Hybrid Deep Reinforcement Learning Approach.
Bharat Bhargava, Mayank Kejriwal · IEEE Transactions on Emerging Topics in Computational Intelligence.
Sara Melotte, Mayank Kejriwal.
Predicting Zip Code-Level Vaccine Hesitancy in US Metropolitan Areas Using Machine Learning Models on Public Tweets.
PLOS Digital Health.
Mayank Kejriwal.
Knowledge Graphs: A Practical Review of the Research Landscape.
MDPI Information.
Akarsh Nagaraj, Mayank Kejriwal.
Dataset for studying gender disparity in English literary texts.
Elsevier Data in Brief.
Mayank Kejriwal.
Artificial Intelligence for Industries of the Future.
Springer, Future of Business and Finance Series.
Mayank Kejriwal, Ravi Kiran Selvam, Chien-Chun Ni, and Nicolas Torzec.
Local Taxonomy Construction: An Information Retrieval Approach Using Representation Learning.
Social Media Analysis for Event Detection · Lecture Notes in Social Networks, Springer Nature · Editor: Ozyer, Tansel.
Mayank Kejriwal.
Knowledge Graphs.
Invited book chapter · Applied Data Science in Tourism, Springer · Editors: Tourism on the Verge, Roman Egger.
Mayank Kejriwal, Yuesheng Luo.
On the Empirical Association between Trade Network Complexity and Global Gross Domestic Product.
The 11th International Conference on Complex Networks and their Applications.
Yuesheng Luo, Mayank Kejriwal.
Understanding COVID-19 Vaccine Reaction through Comparative Analysis on Twitter.
The 2022 Computing Conference, held in London, United Kingdom.
Mayank Kejriwal.
A Pedagogical Framework for Understanding the Alignment Between Classroom Project Evaluations and Real-World Industry Requirements.
The 2022 ASEE Annual Conference, held in Minneapolis.
Katarina Doctor, Christine Task, Eric Kildebeck, Mayank Kejriwal, Lawrence Holder, and Russell Leong.
Toward Defining a Domain Complexity Measure Across Domains.
AAAI Spring Symposium on ‘Designing Artificial Intelligence for Open Worlds’.
Mayank Kejriwal, Ke Shen.
Can Scale-free Network Growth with Triad Formation Capture Simplicial Complex Distributions in Real Communication Networks?.
The 2nd Graphs and More Complex Structures for Learning and Reasoning (GCLR) · workshop held in conjunction with AAAI 2022 · Press (selected only): The Conversation, GCN, Houston Chronicle, phys.org.

2021

Mayank Kejriwal.
Link Prediction between Structured Geopolitical Events: Models and Experiments.
Frontiers in Big Data-Big Data Networks.
Mayank Kejriwal, Ke Shen, Chien-Chun Ni, Nicolas Torzec.
Transfer-Based Taxonomy Induction over Concept Labels.
Engineering Applications of Artificial Intelligence (Elsevier).
Henrique Santos, Mayank Kejriwal, Alice M. Mulvehill, Gretchen Forbush, Deborah L. McGuinness.
An experimental study measuring human annotator categorization agreement on commonsense sentences.
Experimental Results (Cambridge University Press).
Mayank Kejriwal, Qile Wang, Hongyu Li, Lu Wang.
An Empirical Study of Emoji Usage on Twitter in Linguistic and National Contexts.
Online Social Networks and Media · Press (selected only): Global News Canada, CNN Indonesia, IT-daily.net, Diario De Cuyo (Argentina), · Scientias.nl, phys.org, PresseText, then24.com, Market Research Telecast, FTD (Germany), · Forosocuellamos (Spain), exame.com, Upgrade Magazine, Psychomedia, Samachar Central (Canada), · NewsBeezer, IFL Science, studyfinds.org, UniVistaTV.
Mayank Kejriwal, Shilpa Thomas.
A multi-agent simulator for generating novelty in monopoly.
Simulation Modelling Practice and Theory.
Sara Melotte, Mayank Kejriwal.
A Geo-Tagged COVID-19 Twitter Dataset for 10 North American Metropolitan Areas over a 255-Day Period.
MDPI Data.
Mayank Kejriwal, Ke Shen, Chien-Chun Ni, Nicolas Torzec.
An evaluation and annotation methodology for product category matching in e-commerce.
Computers in Industry.
Minda Hu, Ashwin Mohan Rao, Mayank Kejriwal, Kristina Lerman.
Socioeconomic Correlates of Anti-Science Attitudes in the US.
MDPI Future Internet, Special Issue Digital and Social Media in the Disinformation Age.
Minda Hu, Mayank Kejriwal.
Measuring spatio-textual affinities in twitter between two urban metropolises.
Journal of Computational Social Science.
Mayank Kejriwal.
On using centrality to understand importance of entities in the Panama Papers.
PLOS One.
Mayank Kejriwal.
Unsupervised DNF Blocking for Efficient Linking of Knowledge Graphs and Tables.
MDPI Information Journal, Special issue on Knowledge Graphs for Search and Recommendation.
Mayank Kejriwal, Craig Knoblock, and Pedro Szekely.
Knowledge Graphs: Fundamentals, Techniques and Applications.
MIT Press.
Mayank Kejriwal.
Smart Cities.
Invited book chapter · Handbook of Big Geospatial Data, Springer · Editors: Martin Werner, Yao-Yi Chiang.
Mayank Kejriwal and Peilin Zhou.
Visual Exploration and Debugging of Machine Learning Classification over Social Media Data.
Big Data and Social Media Analytics: Trending Applications · Lecture Notes in Social Networks, Springer Nature · Editors: Çakırtaş, Mehmet & Ozdemir, Kemal.
Ke Shen, Mayank Kejriwal.
On the Generalization Abilities of Fine-Tuned Commonsense Language Representation Models.
41st British Computer Society Specialist Group on Artificial Intelligence Conference (AI-2021) · Published in Springer Lecture Notes in Artificial Intelligence (LNAI, volume 13101) · Winner of Best Refereed Technical Paper Award.
Mayank Kejriwal, Ge Fang and Ying Zhou.
A Feasibility Study of Open-Source Sentiment Analysis and Text Classification Systems on Disaster-Specific Social Media Data.
IEEE Symposium Series on Computational Intelligence (SSCI), Data Mining Applications Track.
Mayank Kejriwal, Ravi Kiran Selvam, Chien-Chun Ni and Nicolas Torzec.
Empirical Best Practices On Using Product-Specific Schema.org.
Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI).

2020

Mayank Kejriwal.
A meta-engine for building domain-specific search engines.
Software Impacts Journal.
Mayank Kejriwal.
Knowledge Graphs and COVID-19: Opportunities, Challenges, and Implementation.
Harvard Data Science Review, Special Issue on COVID-19: Unprecedented Challenges and Chances.
Mayank Kejriwal, Akarsh Dang.
Structural studies of the global networks exposed in the Panama papers.
Applied Network Science.
Mayank Kejriwal, Peilin Zhou.
On detecting urgency in short crisis messages using minimal supervision and transfer learning.
Social Network Analysis and Mining.
Mayank Kejriwal, Yao Gu.
Network-theoretic modeling of complex activity using UK online sex advertisements.
Applied Network Science.
Mayank Kejriwal.
AI and Social Good in the Context of Sex Trafficking: Design Space and Best Practices Featured book chapter in the 6th Knowledge Management and Intellectual Capital Excellence Awards: An Anthology of Case Histories 2020.
Book edited by Dan Remenyi.
Mayank Kejriwal.
Domain-specific Search Engines for Investigating Human Trafficking and Other Illicit Activities.
Invited chapter · Encyclopedia of Criminal Activities and the Deep Web · DOI: 10.4018/978-1-5225-9715-5.
Mayank Kejriwal, Ravi Kiran Selvam, Chien-Chun Ni and Nicolas Torzec.
Locally Constructing Product Taxonomies from Scratch Using Representation Learning.
The 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining.
Ravi Kiran Selvam, Mayank Kejriwal.
On using Product-Specific Schema. org from Web Data Commons: An Empirical Set of Best Practices.
KDD Workshop on Knowledge Graphs and E-Commerce.

2019

Mayank Kejriwal, Rahul Kapoor.
Network-theoretic information extraction quality assessment in the human trafficking domain.
Applied Network Science.
Mayank Kejriwal, Yao Gu.
A Pipeline for Rapid Post-Crisis Twitter Data Acquisition, Filtering and Visualization.
MDPI Technologies, Special Issue on Multimedia and Cross-modal Retrieval.
Mayank Kejriwal, Pedro Szekely.
myDIG: Personalized Illicit Domain-Specific Knowledge Discovery with No Programming.
Future Internet.
Mayank Kejriwal.
Domain-specific Knowledge Graph Construction.
Springer Brief.
Multi-disciplinary track.
Concept Drift in Bias and Sensationalism Detection: An Experimental Study.
Shuo Zhang, Mayank Kejriwal · The 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis · and Mining, held in Vancouver, Canada.
Mayank Kejriwal, Peilin Zhou.
Low-supervision urgency detection and transfer in short crisis messages.
The 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis · and Mining, held in Vancouver, Canada.
Mozhdeh Gheini, Mayank Kejriwal.
Unsupervised Product Entity Resolution using Graph Representation Learning.
The ACM 2019 SIGIR Workshop on eCommerce, held in Paris, France.

2018

Daye Nam, Mayank Kejriwal.
How do Organizations Publish Semantic Markup? Three Case Studies Using Public Schema.org Crawls.
IEEE Computer.
Mayank Kejriwal, Pedro Szekely, Craig Knoblock.
Investigative Knowledge Discovery for Combating Illicit Activities.
IEEE Intelligent Systems.
Yuxiao Dong (Microsoft Research, Redmond, CA), Fragkiskos D. Malliaros (CentraleSupelec, France),.
Proceedings of the 2018 International Workshop on Learning Representations for Big Networks (BigNet@WWW2018) co-located with the International World Wide Web Conference (WWW 2018).
Editors: Jie Tang (Tsinghua University, China), Michalis Vazirgiannis (Ecole Polytechnique, France), · Michael Cochez (Fraunhofer FIT, Germany), Mayank Kejriwal (University of Southern California, USA), · Achim Rettinger (Karlsruhe Institute of Technology, Germany).
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Thierry Declerck (DFKI GmbH, Germany), Gerard de Melo (Rutgers University, USA),.
Proceedings of the First Workshop on Deep Learning for Knowledge Graphs and Semantic Technologies (DL4KGS) co-located with the 15th Extended Semantic Web Conference (ESWC 2018).
Editors (Alphabetical Order): Michael Cochez (Fraunhofer Institute for Applied Information Technology, Germany), · Luis Espinosa Anke (Cardiff University, UK), Besnik Fetahu (L3S Research Center, Germany), · Dagmar Gromann (International Center for Computational Logic, Germany), · Mayank Kejriwal (University of Southern California, USA), Maria Koutraki (FIZ-Karlsruhe, Germany), · Freddy Lecue (Accenture, Ireland), Enrico Palumbo (ISMB, Italy), Harald Sack (FIZ-Karlsruhe, Germany) · URN: urn:nbn:de:0074-2106-7.
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Tongtao Zhang, Ananya Subburathinam , Ge Shi , Lifu Huang , Di Lu , Xiaoman Pan ,.
GAIA-A Multi-media Multi-lingual Knowledge Extraction and Hypothesis Generation System.
Manling Li , Boliang Zhang, Qingyun Wang , Spencer Whitehead , Heng Ji, Alireza Zareian , · Hassan Akbari , Brian Chen , Ruiqi Zhong , Steven Shao , Emily Allaway , Shih-Fu Chang , · Kathleen McKeown, Dongyu Li, Xin Huang, Kexuan Sun, Xujun Peng , Ryan Gabbard , · Marjorie Freedman , Mayank Kejriwal , Ram Nevatia , Pedro Szekely, T.K. Satish Kumar, · Ali Sadeghian , Giacomo Bergami , Sourav Dutta , Miguel Rodriguez,, Daisy Zhe Wang · Text Analysis Conference (TAC) KBP track, 2018.
Mayank Kejriwal, Jing Peng, Haotian Zhang and Pedro Szekely.
Structured Event Entity Resolution in Humanitarian Domains.
International Semantic Web Conference (Research Track), held in Monterrey, California.
Yolanda Gil, Ke-Thia Yao, Varun Ratnakar, Daniel Garijo, Greg Ver Steeg, Pedro Szekely,.
P4ML: A Phased Performance-Based Pipeline Planner for Automated Machine Learning.
Robert Brekelmans, Mayank Kejriwal, Fanghao Luo and I-Hui Huang · AutoML Workshop 2018 at ICML, held in Stockholm, Sweden.
Pedro Szekely, Mayank Kejriwal.
Domain-specific Insight Graphs.
International Project track paper at the ACM Web Conference in Lyon, France 2018.
Mayank Kejriwal, Yao Gu.
A Pipeline for Post-Crisis Twitter Data Acquisition.
Workshop on Social Web in Emergency and Disaster Management (SWDM), co-held with the · ACM Web Search and Data Mining (WSDM) Conference in Los Angeles, California.
Kyle Hundman, Thamme Gowda, Mayank Kejriwal and Benedikt Boecking.
Always Lurking: Understanding and Mitigating Bias in Online Human Trafficking Detection.
AAAI/ACM Conference on AI, Ethics and Society (AIES), 2018, held in New Orleans, Louisiana.

2017

Mayank Kejriwal, Pedro Szekely.
Knowledge Graphs for Social Good: An Entity-centric Search Engine for the Human Trafficking Domain.
IEEE Transactions on Big Data, Special Call on Knowledge Graphs.
Mayank Kejriwal, Pedro Szekely.
Scalable Generation of Type Embeddings using the ABox.
Open Journal of Semantic Web.
Xin Luna Dong (Amazon, USA), Ramanathan V. Guha (schema.org, USA), Armin Haller (ANU, Australia),.
Joint Proceedings of the International Workshops on Hybrid Statistical Semantic Understanding and Emerging Semantics, and Semantic Statistics co-located with the 16th International Semantic Web Conference (ISWC 2017).
Editors (Alphabetical Order): Sarven Capadisli (University of Bonn, Germany), Franck Cotton (INSEE, France), · Pascal Hitzler (Wright State University, USA), Evangelos Kalampokis (University of Macedonia, Greece), · Mayank Kejriwal (University of Southern California, USA), Freddy Lecue (Accenture Technology Labs, Ireland), · D. Sivakumar (Google, USA), Pedro Szekely (University of Southern California, USA), · Raphael Troncy (EURECOM, France) and Michael Witbrock (IBM, USA) · URN: urn:nbn:de:0074-1923-2.
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Mayank Kejriwal.
Populating a Linked Data Entity Name System: A Big Data Solution for Unsupervised Instance Matching.
IOS Press, Studies in the Semantic Web Series.
Mayank Kejriwal, Jiayuan Ding, Runqi Shao, Anoop Kumar and Pedro Szekely.
FlagIt: A System for Minimally Supervised Human Trafficking Indicator Mining.
Workshop on Learning with Limited Labeled Data (LLD) at NeurIPS 2017, held in Long Beach, California.
Mayank Kejriwal, Pedro Szekely.
Neural Embeddings for Populated Geonames Locations.
International Semantic Web Conference (Resource Track), held in Vienna, Austria.
Mayank Kejriwal, Pedro Szekely.
An Investigative Search Engine for the Human Trafficking Domain.
International Semantic Web Conference (In-Use Track), held in Vienna, Austria.
Mayank Kejriwal.
Adaptive Candidate Generation for Scalable Edge-discovery Tasks on Data Graphs.
MLG Workshop at ACM KDD, 2017, held in Halifax, Nova Scotia, Canada.
Mayank Kejriwal.
Predicting Role Relevance with Minimal Domain Expertise in a Financial Domain.
DSMM Workshop at ACM SIGMOD, 2017, held in Chicago, Illinois.
Rahul Kapoor, Mayank Kejriwal, Pedro Szekely.
Using Contexts and Constraints for Improved Geotagging of Human Trafficking Webpages.
GeoRich Workshop at ACM SIGMOD, 2017, held in Chicago, Illinois.
Mayank Kejriwal, Pedro Szekely.
Supervised Typing of Big Graphs using Semantic Embeddings.
Semantic Big Data (SBD) Workshop at ACM SIGMOD, 2017, held in Chicago, Illinois.
Mayank Kejriwal, Pedro Szekely.
Information Extraction in Illicit Domains.
ACM World Wide Web Conference, 2017, held in Perth, Australia.

2016

Mayank Kejriwal, Daniel P. Miranker.
Local, Domain-independent Heuristics for the FEIII Challenge: Lessons and Observations.
DSMM Workshop at ACM SIGMOD, 2016, held in San Francisco, California.

2015

Mayank Kejriwal, Daniel P. Miranker.
An Unsupervised Instance Matcher for Schema-free RDF Data.
The Journal of Web Semantics.
Mayank Kejriwal, Qiaoling Liu, Ferosh Jacob and Faizan Javed.
A Pipeline for Extracting and Deduplicating Domain-Specific Knowledge Bases.
Industry track in the IEEE International Conference on Big Data, held in Santa Clara, California.
Mayank Kejriwal, Daniel P. Miranker.
Decision-making Bias in Instance Matching Model Selection.
The 14th International Semantic Web Conference, held in Bethlehem, Pennsylvania.
Mayank Kejriwal, Daniel P. Miranker.
Sorted Neighborhood for Schema-free RDF Data.
Winner of best paper award · The 4th Knowledge Discovery and Data Mining meets Linked Open Data workshop, · The 12th European Semantic Web Conference, held in Portoroz, Slovenia.
Mayank Kejriwal, Daniel P. Miranker.
Semi-supervised Instance Matching using Boosted Classifiers.
The 12th European Semantic Web Conference, held in Portoroz, Slovenia.
Mayank Kejriwal.
Entity Resolution in a Big Data Framework.
Doctoral consortium, the 29th Conference on Artificial Intelligence (AAAI), held in Austin, TX.

2014

Mayank Kejriwal.
Populating Entity Name Systems for Big Data Integration.
The 13th International Semantic Web Conference, held in Riva Del Garda, Italy.
Mayank Kejriwal and Daniel P. Miranker.
A Two-Step Blocking Scheme Learner for Scalable Link Discovery.
The 9th International Workshop on Ontology Matching at the 13th International Semantic Web Conference, held in Riva Del Garda, Italy.
Aibo Tian, Mayank Kejriwal and Daniel P. Miranker.
Schema Matching over Relations, Attributes and Data Values.
The 26th International Conference on Scientific and Statistical Database Management, held in Aalborg, Denmark.

2013

Mayank Kejriwal and Daniel P. Miranker.
An Unsupervised Algorithm for Learning Blocking Schemes.
The 13th IEEE International Conference on Data Mining, held in Dallas, Texas.
Zihao Zhou, Mayank Kejriwal and Risto Miikkulainen.
Extended Scaled Neural Predictor for Improved Branch Prediction.
The IEEE International Conference on Neural Networks, held in Dallas, Texas.

2012

Liana Diesendruck, Luigi Marini, Rob Kooper, Mayank Kejriwal and Kenton McHenry.
A Framework to Access Handwritten Information within Large Digitized Paper Collections.
The 8th IEEE International Conference on eScience, held in Chicago, Illinois.
Digitization and search: A non-traditional use of HPC.