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2020 – today
- 2024
[j31]Navapat Nananukul, Khanin Sisaengsuwanchai, Mayank Kejriwal:
Cost-efficient prompt engineering for unsupervised entity resolution in the product matching domain. Discov. Artif. Intell. 4(1): 56 (2024)- [j30]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 Intell. 6(1): 1-28 (2024) - [j29]Mayank Kejriwal, Eric J. Kildebeck, Robert J. Steininger, Abhinav Shrivastava:
Challenges, evaluation and opportunities for open-world learning. Nat. Mac. Intell. 6(6): 580-588 (2024) - [j28]Mayank Kejriwal, Victoria Petryshyn:
Advancing computational sustainability in higher education. Nat. Comput. Sci. 4(6): 382-383 (2024) - [c61]Adin Aberbach, Mayank Kejriwal, Ke Shen:
Multipartite Entity Resolution: Motivating a K-Tuple Perspective (Student Abstract). AAAI 2024: 23434-23435 - [c60]Xiyao Cheng, Lakshmi Srinivas Edara, Yuanxun Zhang, Mayank Kejriwal, Prasad Calyam:
Influence Role Recognition and LLM-Based Scholar Recommendation in Academic Social Networks. DSAA 2024: 1-11 - [c59]Mayank Kejriwal:
Designing Social Good Semantic Computing Architectures for the Long Tail: Case Studies, Evaluation, and Challenges. ICSC 2024: 253-260 - [c58]Mayank Kejriwal, Hamid Haidarian, Min-Hsueh Chiu, Andy Xiang, Deep Shrestha, Faizan Javed:
A Semantic Search Engine for Helping Patients Find Doctors and Locations in a Large Healthcare Organization. SIGIR 2024: 2945-2949 - [e6]Sanju Tiwari, Nandana Mihindukulasooriya, Francesco Osborne, Dimitris Kontokostas, Jennifer D'Souza, Mayank Kejriwal, Maria Angela Pellegrino, Anisa Rula, José Emilio Labra Gayo, Michael Cochez, Mehwish Alam:
Joint proceedings of the 3rd International workshop on knowledge graph generation from text (TEXT2KG) and Data Quality meets Machine Learning and Knowledge Graphs (DQMLKG) co-located with the Extended Semantic Web Conference ( ESWC 2024), Hersonissos, Greece, May 26-30, 2024. CEUR Workshop Proceedings 3747, CEUR-WS.org 2024 [contents] - [i44]Zhisheng Tang, Ke Shen, Mayank Kejriwal:
An Evaluation of Estimative Uncertainty in Large Language Models. CoRR abs/2405.15185 (2024) - [i43]Yongyi Ji, Zhisheng Tang, Mayank Kejriwal:
Is persona enough for personality? Using ChatGPT to reconstruct an agent's latent personality from simple descriptions. CoRR abs/2406.12216 (2024) - [i42]Zhisheng Tang, Mayank Kejriwal:
GRASP: A Grid-Based Benchmark for Evaluating Commonsense Spatial Reasoning. CoRR abs/2407.01892 (2024) - [i41]Ke Shen, Mayank Kejriwal:
Defining and Evaluating Decision and Composite Risk in Language Models Applied to Natural Language Inference. CoRR abs/2408.01935 (2024) - [i40]Ke Shen, Mayank Kejriwal:
SelECT-SQL: Self-correcting ensemble Chain-of-Thought for Text-to-SQL. CoRR abs/2409.10007 (2024) - 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 - [j27]Zhisheng Tang, Mayank Kejriwal:
Evaluating deep generative models on cognitive tasks: a case study. Discov. Artif. Intell. 3(1) (2023) - [j26]Ke Shen, Mayank Kejriwal:
An experimental study measuring the generalization of fine-tuned language representation models across commonsense reasoning benchmarks. Expert Syst. J. Knowl. Eng. 40(5) (2023) - [c57]Mayank Kejriwal, Henrique Santos, Ke Shen, Alice M. Mulvehill, Deborah L. McGuinness:
Context-Rich Evaluation of Machine Common Sense. AGI 2023: 167-176 - [c56]Zhisheng Tang, Mayank Kejriwal:
Can Language Models Be Used in Multistep Commonsense Planning Domains? AGI 2023: 276-285 - [c55]Prasad Calyam, Mayank Kejriwal, Praveen Rao, Jianlin Cheng, Weichao Wang, Linquan Bai, V. Sriram Siddhardh Nadendla, Sanjay Madria, Sajal K. Das, Rohit Chadha, Khaza Anuarul Hoque, Kannappan Palaniappan, Kiran Neupane, Roshan Lal Neupane, Sankeerth Gandhari, Mukesh Singhal, Lotfi Ben Othmane, Meng Yu, Vijay Anand, Bharat K. Bhargava, Brett Robertson, Kerk F. Kee, Patrice Buzzanell, Natalie A. Bolton, Harsh Taneja:
Towards a Domain-Agnostic Knowledge Graph-as-a-Service Infrastructure for Active Cyber Defense with Intelligent Agents. AIPR 2023: 1-8 - [c54]Yidan Sun, Mayank Kejriwal:
DeepGraph: Multi-Cluster Interactive Visualization of Complex Networks in a Learned Representation Space. ASONAM 2023: 427-430 - [c53]Yidan Sun, Mayank Kejriwal:
A structural study of Big Tech firm-switching of inventors in the post-recession era. ASONAM 2023: 670-677 - [c52]Ke Shen, Mayank Kejriwal:
An Analytical Approximation of Simplicial Complex Distributions in Communication Networks. COMPLEX NETWORKS (4) 2023: 16-26 - [c51]Min-Hsueh Chiu, Mayank Kejriwal:
A Model and Structural Analysis of Networked Bitcoin Transaction Flows. COMPLEX NETWORKS (3) 2023: 456-467 - [c50]Xiyao Cheng, Yuanxun Zhang, Harsh Joshi, Mayank Kejriwal, Prasad Calyam:
Knowledge Graph-based Embedding for Connecting Scholars in Academic Social Networks. DSAA 2023: 1-10 - [c49]Ke Shen, Mayank Kejriwal:
Substructure Discovery in Commonsense Relations Using Graph Representation Learning. IntelliSys (1) 2023: 714-734 - [c48]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. KGSWC 2023: 151-167 - [e5]Sanju Tiwari, Nandana Mihindukulasooriya, Francesco Osborne, Dimitris Kontokostas, Jennifer D'Souza, Mayank Kejriwal, Edgard Marx:
Joint Proceedings of the Second International Workshop on Knowledge Graph Generation From Text and the First International BiKE Challenge co-located with 20th Extended Semantic Conference (ESWC 2023), Hersonissos, Greece, May 29th, 2023. CEUR Workshop Proceedings 3447, CEUR-WS.org 2023 [contents] - [d4]Henrique Santos, Alice M. Mulvehill, Ke Shen, Mayank Kejriwal, Deborah L. McGuinness:
TG-CSR Annotations. Zenodo, 2023
- [d3]Henrique Santos, Ke Shen, Alice M. Mulvehill, Mayank Kejriwal, Deborah L. McGuinness:
TG-CSR: Theoretically-Grounded Commonsense Reasoning Benchmark. Version 1.0. Zenodo, 2023 [all versions] - [d2]Henrique Santos, Ke Shen, Alice M. Mulvehill, Mayank Kejriwal, Deborah L. McGuinness:
TG-CSR: Theoretically-Grounded Commonsense Reasoning Benchmark. Version 1.1. Zenodo, 2023 [all versions] - [d1]Henrique Santos, Ke Shen, Alice M. Mulvehill, Mayank Kejriwal, Deborah L. McGuinness:
TG-CSR: Theoretically-Grounded Commonsense Reasoning Benchmark. Version 1.2. Zenodo, 2023 [all versions] - [i39]Zhisheng Tang, Mayank Kejriwal:
A Pilot Evaluation of ChatGPT and DALL-E 2 on Decision Making and Spatial Reasoning. CoRR abs/2302.09068 (2023) - [i38]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) - [i37]Yidan Sun, Mayank Kejriwal:
A structural study of Big Tech firm-switching of inventors in the post-recession era. CoRR abs/2307.07920 (2023) - [i36]Mayank Kejriwal:
Named Entity Resolution in Personal Knowledge Graphs. CoRR abs/2307.12173 (2023) - [i35]Ke Shen, Mayank Kejriwal:
A Formalism and Approach for Improving Robustness of Large Language Models Using Risk-Adjusted Confidence Scores. CoRR abs/2310.03283 (2023) - [i34]Mayank Kejriwal, Hamid Haidarian, Min-Hsueh Chiu, Andy Xiang, Deep Shrestha, Faizan Javed:
A Knowledge Graph-Based Search Engine for Robustly Finding Doctors and Locations in the Healthcare Domain. CoRR abs/2310.05258 (2023) - [i33]Khanin Sisaengsuwanchai, Navapat Nananukul, Mayank Kejriwal:
How does prompt engineering affect ChatGPT performance on unsupervised entity resolution? CoRR abs/2310.06174 (2023) - [i32]Navapat Nananukul, Mayank Kejriwal:
HALO: An Ontology for Representing Hallucinations in Generative Models. CoRR abs/2312.05209 (2023) - [i31]Katarina Doctor, Mayank Kejriwal, Lawrence Holder, Eric J. Kildebeck, Emma Resmini, Christopher Pereyda, Robert J. Steininger, Daniel V. Olivença:
Understanding and Estimating Domain Complexity Across Domains. CoRR abs/2312.13487 (2023) - 2022
- [j25]Mayank Kejriwal, Ke Shen, Chien-Chun Ni, Nicolas Torzec:
Transfer-based taxonomy induction over concept labels. Eng. Appl. Artif. Intell. 108: 104548 (2022) - [j24]Mayank Kejriwal:
Knowledge Graphs: A Practical Review of the Research Landscape. Inf. 13(4): 161 (2022) - [j23]Minda Hu, Mayank Kejriwal:
Measuring spatio-textual affinities in twitter between two urban metropolises. J. Comput. Soc. Sci. 5(1): 227-252 (2022) - [j22]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) - [j21]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) - [j20]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) - [c47]Mayank Kejriwal, Zhisheng Tang:
Evaluating Language Representation Models on Approximately Rational Decision Making Problems. CogSci 2022 - [c46]Mayank Kejriwal, Yuesheng Luo:
On the Empirical Association Between Trade Network Complexity and Global Gross Domestic Product. COMPLEX NETWORKS (1) 2022: 456-466 - [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
- [j19]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) - [j18]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) - [j17]Mayank Kejriwal:
Link Prediction Between Structured Geopolitical Events: Models and Experiments. Frontiers Big Data 4: 779792 (2021) - [j16]Minda Hu, Ashwin Rao, Mayank Kejriwal, Kristina Lerman:
Socioeconomic Correlates of Anti-Science Attitudes in the US. Future Internet 13(6): 160 (2021) - [j15]Mayank Kejriwal:
Unsupervised DNF Blocking for Efficient Linking of Knowledge Graphs and Tables. Inf. 12(3): 134 (2021) - [j14]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) - [j13]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 López:
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]