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2020 – today
- 2023
[b3]Mayank Kejriwal:
Artificial Intelligence for Industries of the Future - Beyond Facebook, Amazon, Microsoft and Google. Springer 2023, ISBN 978-3-031-19038-4, pp. 1-136- [i32]Zhisheng Tang, Mayank Kejriwal:
A Pilot Evaluation of ChatGPT and DALL-E 2 on Decision Making and Spatial Reasoning. CoRR abs/2302.09068 (2023) - [i31]Katarina Doctor, Christine Task, Eric J. Kildebeck, Mayank Kejriwal, Lawrence Holder, Russell Leong:
Toward Defining a Domain Complexity Measure Across Domains. CoRR abs/2303.04141 (2023) - 2022
- [j22]Mayank Kejriwal
, Ke Shen, Chien-Chun Ni, Nicolas Torzec:
Transfer-based taxonomy induction over concept labels. Eng. Appl. Artif. Intell. 108: 104548 (2022) - [j21]Mayank Kejriwal:
Knowledge Graphs: A Practical Review of the Research Landscape. Inf. 13(4): 161 (2022) - [j20]Mayank Kejriwal, Henrique Santos, Alice M. Mulvehill, Deborah L. McGuinness:
Designing a strong test for measuring true common-sense reasoning. Nat. Mach. Intell. 4(4): 318-322 (2022) - [j19]Mayank Kejriwal, Pedro A. Szekely:
Knowledge Graphs for Social Good: An Entity-Centric Search Engine for the Human Trafficking Domain. IEEE Trans. Big Data 8(3): 592-606 (2022) - [j18]Trevor Bonjour, Marina Haliem, Aala Oqab Alsalem, Shilpa Thomas, Hongyu Li, Vaneet Aggarwal, Mayank Kejriwal, Bharat K. Bhargava:
Decision Making in Monopoly Using a Hybrid Deep Reinforcement Learning Approach. IEEE Trans. Emerg. Top. Comput. Intell. 6(6): 1335-1344 (2022) - [c45]Yuesheng Luo, Mayank Kejriwal:
Understanding COVID-19 Vaccine Reaction Through Comparative Analysis on Twitter. SAI (1) 2022: 846-864 - [e4]Sanju Tiwari, Nandana Mihindukulasooriya, Francesco Osborne, Dimitris Kontokostas, Jennifer D'Souza, Mayank Kejriwal, Loris Bozzato, Valentina Anita Carriero, Torsten Hahmann, Antoine Zimmermann:
Proceedings of the 1st International Workshop on Knowledge Graph Generation From Text and the 1st International Workshop on Modular Knowledge co-located with 19th Extended Semantic Conference (ESWC 2022), Hersonissos, Greece, May 30th, 2022. CEUR Workshop Proceedings 3184, CEUR-WS.org 2022 [contents] - [i30]Mayank Kejriwal, Ke Shen:
Can Scale-free Network Growth with Triad Formation Capture Simplicial Complex Distributions in Real Communication Networks? CoRR abs/2203.06491 (2022) - [i29]Henrique Santos, Ke Shen, Alice M. Mulvehill, Yasaman Razeghi, Deborah L. McGuinness, Mayank Kejriwal:
A Theoretically Grounded Benchmark for Evaluating Machine Commonsense. CoRR abs/2203.12184 (2022) - [i28]Akarsh Nagaraj, Mayank Kejriwal:
Robust Quantification of Gender Disparity in Pre-Modern English Literature using Natural Language Processing. CoRR abs/2204.05872 (2022) - [i27]Ke Shen, Mayank Kejriwal:
Understanding Prior Bias and Choice Paralysis in Transformer-based Language Representation Models through Four Experimental Probes. CoRR abs/2210.01258 (2022) - [i26]Ke Shen, Mayank Kejriwal:
Understanding Substructures in Commonsense Relations in ConceptNet. CoRR abs/2210.01263 (2022) - [i25]Zhisheng Tang, Mayank Kejriwal:
Can Language Representation Models Think in Bets? CoRR abs/2210.07519 (2022) - [i24]Mayank Kejriwal, Yuesheng Luo:
On the Empirical Association between Trade Network Complexity and Global Gross Domestic Product. CoRR abs/2211.13117 (2022) - 2021
- [j17]Mayank Kejriwal, Ke Shen, Chien-Chun Ni, Nicolas Torzec:
An evaluation and annotation methodology for product category matching in e-commerce. Comput. Ind. 131: 103497 (2021) - [d2]Sara Melotte, Mayank Kejriwal:
A Geo-Tagged COVID-19 Twitter Dataset for 10 North American Metropolitan Areas over a 255-Day Period. Data 6(6): 64 (2021) - [j16]Mayank Kejriwal:
Link Prediction Between Structured Geopolitical Events: Models and Experiments. Frontiers Big Data 4: 779792 (2021) - [j15]Minda Hu, Ashwin Rao, Mayank Kejriwal, Kristina Lerman:
Socioeconomic Correlates of Anti-Science Attitudes in the US. Future Internet 13(6): 160 (2021) - [j14]Mayank Kejriwal:
Unsupervised DNF Blocking for Efficient Linking of Knowledge Graphs and Tables. Inf. 12(3): 134 (2021) - [j13]Mayank Kejriwal, Qile Wang, Hongyu Li, Lu Wang:
An empirical study of emoji usage on Twitter in linguistic and national contexts. Online Soc. Networks Media 24: 100149 (2021) - [d1]Mayank Kejriwal:
A meta-engine for building domain-specific search engines. Softw. Impacts 7: 100052 (2021) - [j12]Mayank Kejriwal, Shilpa Thomas:
A multi-agent simulator for generating novelty in monopoly. Simul. Model. Pract. Theory 112: 102364 (2021) - [c44]Mayank Kejriwal, Ravi Kiran Selvam, Chien-Chun Ni, Nicolas Torzec:
Empirical Best Practices On Using Product-Specific Schema.org. AAAI 2021: 15452-15457 - [c43]Mayank Kejriwal, Ke Shen:
Unsupervised real-time induction and interactive visualization of taxonomies over domain-specific concepts. ASONAM 2021: 301-304 - [c42]Ke Shen, Mayank Kejriwal:
On the Generalization Abilities of Fine-Tuned Commonsense Language Representation Models. SGAI Conf. 2021: 3-16 - [c41]Mayank Kejriwal, Ge Fang, Ying Zhou:
A Feasibility Study of Open-Source Sentiment Analysis and Text Classification Systems on Disaster-Specific Social Media Data. SSCI 2021: 1-8 - [i23]Marina Haliem, Trevor Bonjour, Aala Oqab Alsalem, Shilpa Thomas, Hongyu Li, Vaneet Aggarwal, Bharat K. Bhargava, Mayank Kejriwal:
Learning Monopoly Gameplay: A Hybrid Model-Free Deep Reinforcement Learning and Imitation Learning Approach. CoRR abs/2103.00683 (2021) - [i22]Sara Melotte, Mayank Kejriwal:
Predicting Zip Code-Level Vaccine Hesitancy in US Metropolitan Areas Using Machine Learning Models on Public Tweets. CoRR abs/2108.01699 (2021) - [i21]Yuesheng Luo, Mayank Kejriwal:
Understanding COVID-19 Vaccine Reaction through Comparative Analysis on Twitter. CoRR abs/2111.05823 (2021) - 2020
- [j11]Mayank Kejriwal, Yao Gu:
Network-theoretic modeling of complex activity using UK online sex advertisements. Appl. Netw. Sci. 5(1): 30 (2020) - [j10]Mayank Kejriwal, Akarsh Dang:
Structural studies of the global networks exposed in the Panama papers. Appl. Netw. Sci. 5(1): 63 (2020) - [j9]Mayank Kejriwal, Peilin Zhou:
On detecting urgency in short crisis messages using minimal supervision and transfer learning. Soc. Netw. Anal. Min. 10(1): 58 (2020) - [c40]Mayank Kejriwal, Ravi Kiran Selvam, Chien-Chun Ni, Nicolas Torzec:
Locally Constructing Product Taxonomies from Scratch Using Representation Learning. ASONAM 2020: 507-514 - [i20]Ravi Kiran Selvam, Mayank Kejriwal:
On using Product-Specific Schema.org from Web Data Commons: An Empirical Set of Best Practices. CoRR abs/2007.13829 (2020) - [i19]Jiayuan Ding, Mayank Kejriwal:
An Experimental Study of The Effects of Position Bias on Emotion CauseExtraction. CoRR abs/2007.15066 (2020) - [i18]Mayank Kejriwal, Ke Shen:
Do Fine-tuned Commonsense Language Models Really Generalize? CoRR abs/2011.09159 (2020) - [i17]Ke Shen, Mayank Kejriwal:
A Data-Driven Study of Commonsense Knowledge using the ConceptNet Knowledge Base. CoRR abs/2011.14084 (2020)
2010 – 2019
- 2019
- [b2]Mayank Kejriwal:
Domain-Specific Knowledge Graph Construction. Springer Briefs in Computer Science, Springer 2019, ISBN 978-3-030-12374-1, pp. 1-87 - [j8]Mayank Kejriwal, Rahul Kapoor:
Network-theoretic information extraction quality assessment in the human trafficking domain. Appl. Netw. Sci. 4(1): 44:1-44:26 (2019) - [j7]Mayank Kejriwal, Pedro A. Szekely:
myDIG: Personalized Illicit Domain-Specific Knowledge Discovery with No Programming. Future Internet 11(3): 59 (2019) - [j6]Mayank Kejriwal, Juan F. Sequeda, Vanessa Lopez:
Knowledge graphs: Construction, management and querying. Semantic Web 10(6): 961-962 (2019) - [c39]Mayank Kejriwal, Peilin Zhou:
Low-supervision urgency detection and transfer in short crisis messages. ASONAM 2019: 353-356 - [c38]Shuo Zhang, Mayank Kejriwal:
Concept drift in bias and sensationalism detection: an experimental study. ASONAM 2019: 601-604 - [c37]Mayank Kejriwal, Peilin Zhou:
SAVIZ: interactive exploration and visualization of situation labeling classifiers over crisis social media data. ASONAM 2019: 705-708 - [c36]Mayank Kejriwal, Pedro A. Szekely:
Co-LOD: Continuous Space Linked Open Data. ISWC (Satellites) 2019: 333-337 - [c35]Mozhdeh Gheini, Mayank Kejriwal:
Unsupervised Product Entity Resolution using Graph Representation Learning. eCOM@SIGIR 2019 - [c34]Mayank Kejriwal, Runqi Shao, Pedro A. Szekely:
Expert-Guided Entity Extraction using Expressive Rules. SIGIR 2019: 1353-1356 - [e3]Mayank Kejriwal, Pedro A. Szekely, Raphaël Troncy:
Proceedings of the 10th International Conference on Knowledge Capture, K-CAP 2019, Marina Del Rey, CA, USA, November 19-21, 2019. ACM 2019, ISBN 978-1-4503-7008-0 [contents] - [i16]Mayank Kejriwal, Peilin Zhou:
Low-supervision urgency detection and transfer in short crisis messages. CoRR abs/1907.06745 (2019) - 2018
- [j5]Daye Nam, Mayank Kejriwal:
How Do Organizations Publish Semantic Markup? Three Case Studies Using Public Schema.org Crawls. Computer 51(6): 42-51 (2018) - [j4]Mayank Kejriwal, Pedro A. Szekely, Craig A. Knoblock:
Investigative Knowledge Discovery for Combating Illicit Activities. IEEE Intell. Syst. 33(1): 53-63 (2018) - [c33]Mayank Kejriwal, Pedro A. Szekely:
Constructing Domain-Specific Search Engines With No Programming. AAAI 2018: 8204-8205 - [c32]Kyle Hundman, Thamme Gowda, Mayank Kejriwal, Benedikt Boecking:
Always Lurking: Understanding and Mitigating Bias in Online Human Trafficking Detection. AIES 2018: 137-143 - [c31]Mayank Kejriwal, Pedro A. Szekely:
Technology-assisted Investigative Search: A Case Study from an Illicit Domain. CHI Extended Abstracts 2018 - [c30]Mayank Kejriwal, Jing Peng, Haotian Zhang, Pedro A. Szekely:
Structured Event Entity Resolution in Humanitarian Domains. ISWC (1) 2018: 233-249 - [c29]Mayank Kejriwal, Daniel Gilley, Pedro A. Szekely, Jill Crisman:
THOR: Text-enabled Analytics for Humanitarian Operations. WWW (Companion Volume) 2018: 147-150 - [c28]Pedro A. Szekely, Mayank Kejriwal:
Domain-specific Insight Graphs (DIG). WWW (Companion Volume) 2018: 433-434 - [c27]Jie Tang, Michalis Vazirgiannis, Yuxiao Dong, Fragkiskos D. Malliaros, Michael Cochez, Mayank Kejriwal, Achim Rettinger:
BigNet 2018 Chairs' Welcome & Organization. WWW (Companion Volume) 2018: 943-944 - [e2]Michael Cochez, Thierry Declerck, Gerard de Melo, Luis Espinosa Anke, Besnik Fetahu, Dagmar Gromann, Mayank Kejriwal, Maria Koutraki, Freddy Lécué, Enrico Palumbo, Harald Sack:
Proceedings of the First Workshop on Deep Learning for Knowledge Graphs and Semantic Technologies (DL4KGS) co-located with the 15th Extended Semantic Web Conerence (ESWC 2018), Heraklion, Crete, Greece, June 4, 2018. CEUR Workshop Proceedings 2106, CEUR-WS.org 2018 [contents] - [i15]Tongtao Zhang, Ananya Subburathinam, Ge Shi, Lifu Huang, Di Lu, Xiaoman Pan, 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 R. McKeown, Dongyu Li, Xin Huang, Kexuan Sun, Xujun Peng, Ryan Gabbard, Marjorie Freedman, Mayank Kejriwal, Ram Nevatia, Pedro A. Szekely, T. K. Satish Kumar, Ali Sadeghian, Giacomo Bergami, Sourav Dutta, Miguel E. Rodríguez, Daisy Zhe Wang:
GAIA - A Multi-media Multi-lingual Knowledge Extraction and Hypothesis Generation System. TAC 2018 - [i14]Mayank Kejriwal, Yao Gu:
A Pipeline for Post-Crisis Twitter Data Acquisition. CoRR abs/1801.05881 (2018) - [i13]Yao Gu, Mayank Kejriwal:
Unsupervised Hashtag Retrieval and Visualization for Crisis Informatics. CoRR abs/1801.05906 (2018) - 2017
- [b1]Mayank Kejriwal:
Populating a Linked Data Entity Name System - A Big Data Solution to Unsupervised Instance Matching. University of Texas at Austin, United States of America, Studies on the Semantic Web 27, IOS Press 2017, ISBN 978-1-61499-691-0, pp. 1-178 - [j3]Mayank Kejriwal:
Populating a linked data entity name system. AI Matters 3(2): 22-23 (2017) - [j2]Mayank Kejriwal, Pedro A. Szekely:
Scalable Generation of Type Embeddings Using the ABox. Open J. Semantic Web 4(1): 20-34 (2017) - [c26]Mayank Kejriwal, Pedro A. Szekely:
Neural Embeddings for Populated Geonames Locations. ISWC (2) 2017: 139-146 - [c25]Mayank Kejriwal, Pedro A. Szekely:
An Investigative Search Engine for the Human Trafficking Domain. ISWC (2) 2017: 247-262 - [c24]Mayank Kejriwal, Thomas Schellenberg, Pedro A. Szekely:
A Semantic Search Engine For Investigating Human Trafficking. ISWC (Posters, Demos & Industry Tracks) 2017 - [c23]Rahul Kapoor, Mayank Kejriwal, Pedro A. Szekely:
Using contexts and constraints for improved geotagging of human trafficking webpages. GeoRich@SIGMOD 2017: 3:1-3:6 - [c22]Mayank Kejriwal, Pedro A. Szekely:
Supervised typing of big graphs using semantic embeddings. SBD@SIGMOD 2017: 3:1-3:6 - [c21]Mayank Kejriwal:
Predicting Role Relevance with Minimal Domain Expertise in a Financial Domain. DSMM@SIGMOD 2017: 10:1-10:2 - [c20]Mayank Kejriwal, Pedro A. Szekely:
Information Extraction in Illicit Web Domains. WWW 2017: 997-1006 - [e1]Sarven Capadisli, Franck Cotton, Xin Luna Dong, Ramanathan V. Guha, Armin Haller, Pascal Hitzler, Evangelos Kalampokis, Mayank Kejriwal, Freddy Lécué, D. Sivakumar, Pedro A. Szekely, Raphaël Troncy, Michael J. Witbrock:
Joint Proceedings of the International Workshops on Hybrid Statistical Semantic Understanding and Emerging Semantics, and Semantic Statistics co-located with 16th International Semantic Web Conference, HybridSemStats@ISWC 2017, Vienna, Austria October 22nd, 2017. CEUR Workshop Proceedings, CEUR-WS.org 2017 [contents] - [i12]Mayank Kejriwal, Pedro A. Szekely:
Information Extraction in Illicit Domains. CoRR abs/1703.03097 (2017) - [i11]Mayank Kejriwal, Pedro A. Szekely:
Supervised Typing of Big Graphs using Semantic Embeddings. CoRR abs/1703.07805 (2017) - [i10]Rahul Kapoor, Mayank Kejriwal, Pedro A. Szekely:
Using Contexts and Constraints for Improved Geotagging of Human Trafficking Webpages. CoRR abs/1704.05569 (2017) - [i9]Mayank Kejriwal:
Predicting Role Relevance with Minimal Domain Expertise in a Financial Domain. CoRR abs/1704.05571 (2017) - [i8]Kyle Hundman, Thamme Gowda, Mayank Kejriwal, Benedikt Boecking:
Always Lurking: Understanding and Mitigating Bias in Online Human Trafficking Detection. CoRR abs/1712.00846 (2017) - [i7]Mayank Kejriwal, Jiayuan Ding, Runqi Shao, Anoop Kumar, Pedro A. Szekely:
FlagIt: A System for Minimally Supervised Human Trafficking Indicator Mining. CoRR abs/1712.03086 (2017) - 2016
- [c19]Mayank Kejriwal, Daniel P. Miranker:
Local, Domain-independent Heuristics for the FEIII Challenge: Lessons and Observations. DSMM@SIGMOD 2016: 17:1-17:2 - [i6]Mayank Kejriwal:
Disjunctive Normal Form Schemes for Heterogeneous Attributed Graphs. CoRR abs/1605.00686 (2016) - [i5]Mayank Kejriwal, Daniel P. Miranker:
Self-contained NoSQL Resources for Cross-Domain RDF. CoRR abs/1608.04437 (2016) - [i4]Mayank Kejriwal, Daniel P. Miranker:
Experience: Type alignment on DBpedia and Freebase. CoRR abs/1608.04442 (2016) - [i3]Janani Balaji, Faizan Javed, Mayank Kejriwal, Chris Min, Sam Sander, Ozgur Ozturk:
An Ensemble Blocking Scheme for Entity Resolution of Large and Sparse Datasets. CoRR abs/1609.06265 (2016) - 2015
- [j1]Mayank Kejriwal, Daniel P. Miranker:
An unsupervised instance matcher for schema-free RDF data. J. Web Semant. 35: 102-123 (2015) - [c18]Mayank Kejriwal:
Sorted Neighborhood for the Semantic Web. AAAI 2015: 4174-4175 - [c17]Mayank Kejriwal:
Entity Resolution in a Big Data Framework. AAAI 2015: 4243-4244 - [c16]Mayank Kejriwal, Qiaoling Liu, Ferosh Jacob, Faizan Javed:
A pipeline for extracting and deduplicating domain-specific knowledge bases. IEEE BigData 2015: 1144-1153 - [c15]Mayank Kejriwal, Daniel P. Miranker:
Sorted Neighborhood for Schema-free RDF Data. KNOW@LOD 2015 - [c14]Mayank Kejriwal, Daniel P. Miranker:
Minimally Supervised Instance Matching: An Alternate Approach. ESWC (Satellite Events) 2015: 72-76 - [c13]Mayank Kejriwal, Daniel P. Miranker:
Sorted Neighborhood for Schema-Free RDF Data. ESWC (Satellite Events) 2015: 217-229 - [c12]Mayank Kejriwal, Daniel P. Miranker:
Semi-supervised Instance Matching Using Boosted Classifiers. ESWC 2015: 388-402 - [c11]Mayank Kejriwal, Daniel P. Miranker:
Decision-Making Bias in Instance Matching Model Selection. ISWC (1) 2015: 392-407 - [i2]Mayank Kejriwal, Daniel P. Miranker:
A DNF Blocking Scheme Learner for Heterogeneous Datasets. CoRR abs/1501.01694 (2015) - [i1]Mayank Kejriwal, Daniel P. Miranker:
On the Complexity of Sorted Neighborhood. CoRR abs/1501.01696 (2015) - 2014
- [c10]Mayank Kejriwal, Daniel P. Miranker:
A two-step blocking scheme learner for scalable link discovery. OM 2014: 49-60 - [c9]Mayank Kejriwal, Daniel P. Miranker:
On Linking Heterogeneous Dataset Collections. ISWC (Posters & Demos) 2014: 217-220 - [c8]Mayank Kejriwal:
Populating Entity Name Systems for Big Data Integration. ISWC (2) 2014: 521-528 - [c7]Aibo Tian, Mayank Kejriwal, Daniel P. Miranker:
Schema matching over relations, attributes, and data values. SSDBM 2014: 28:1-28:12 - 2013
- [c6]Mayank Kejriwal, Daniel P. Miranker:
An Unsupervised Algorithm for Learning Blocking Schemes. ICDM 2013: 340-349 - [c5]Zihao Zhou, Mayank Kejriwal, Risto Miikkulainen:
Extended scaled neural predictor for improved branch prediction. IJCNN 2013: 1-7 - 2012
- [c4]Liana Diesendruck, Luigi Marini, Rob Kooper, Mayank Kejriwal, Kenton McHenry:
A framework to access handwritten information within large digitized paper collections. eScience 2012: 1-10 - [c3]Liana Diesendruck, Luigi Marini, Rob Kooper, Mayank Kejriwal, Kenton McHenry:
Digitization and search: A non-traditional use of HPC. eScience 2012: 1-6 - [c2]Liana Diesendruck, Luigi Marini, Rob Kooper, Mayank Kejriwal, Kenton McHenry:
Abstract: Digitization and Search: A Non-Traditional Use of HPC. SC Companion 2012: 1460-1461 - [c1]Liana Diesendruck, Luigi Marini, Rob Kooper, Mayank Kejriwal, Kenton McHenry:
Poster: Digitization and Search: A Non-Traditional Use of HPC. SC Companion 2012: 1462
Coauthor Index
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