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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 15 of 15 1 Engineering Knowledge Graph from Patent Database ... Siddharth, L; Blessing, Lucienne T. M.; Wood, Kristin L.. - : arXiv, 2021 BASE Show details 2 TargetUM: Targeted High-Utility Itemset Querying ... Miao, Jinbao; Wan, Shicheng; Gan, Wensheng. - : arXiv, 2021 BASE Show details 3 Complex Event Forecasting with Prediction Suffix Trees: Extended Technical Report ... Alevizos, Elias; Artikis, Alexander; Paliouras, Georgios. - : arXiv, 2021 BASE Show details 4 Querying and Repairing Inconsistent Prioritized Knowledge Bases: Complexity Analysis and Links with Abstract Argumentation ... Bienvenu, Meghyn; Bourgaux, Camille. - : arXiv, 2020 BASE Show details 5 ColloQL: Robust Cross-Domain Text-to-SQL Over Search Queries ... Radhakrishnan, Karthik; Srikantan, Arvind; Lin, Xi Victoria. - : arXiv, 2020 Abstract: Translating natural language utterances to executable queries is a helpful technique in making the vast amount of data stored in relational databases accessible to a wider range of non-tech-savvy end users. Prior work in this area has largely focused on textual input that is linguistically correct and semantically unambiguous. However, real-world user queries are often succinct, colloquial, and noisy, resembling the input of a search engine. In this work, we introduce data augmentation techniques and a sampling-based content-aware BERT model (ColloQL) to achieve robust text-to-SQL modeling over natural language search (NLS) questions. Due to the lack of evaluation data, we curate a new dataset of NLS questions and demonstrate the efficacy of our approach. ColloQL's superior performance extends to well-formed text, achieving 84.9% (logical) and 90.7% (execution) accuracy on the WikiSQL dataset, making it, to the best of our knowledge, the highest performing model that does not use execution guided decoding. ... : IntEx-SemPar Workshop at EMNLP 2020, 12 pages, 3 figures ... Keyword: Artificial Intelligence cs.AI; Computation and Language cs.CL; Databases cs.DB; FOS Computer and information sciences; Information Retrieval cs.IR URL: https://arxiv.org/abs/2010.09927 https://dx.doi.org/10.48550/arxiv.2010.09927 BASE Hide details 6 A Hybrid Semantic Parsing Approach for Tabular Data Analysis ... Gao, Yan; Lou, Jian-Guang; Zhang, Dongmei. - : arXiv, 2019 BASE Show details 7 How to define co-occurrence in different domains of study? ... Roche, Mathieu. - : arXiv, 2019 BASE Show details 8 Schema Matching using Machine Learning ... Sahay, Tanvi; Mehta, Ankita; Jadon, Shruti. - : arXiv, 2019 BASE Show details 9 CLaRO: a Data-driven CNL for Specifying Competency Questions ... Keet, C. Maria; Mahlaza, Zola; Antia, Mary-Jane. - : arXiv, 2019 BASE Show details 10 Competency Questions and SPARQL-OWL Queries Dataset and Analysis ... Wisniewski, Dawid; Potoniec, Jedrzej; Lawrynowicz, Agnieszka. - : arXiv, 2018 BASE Show details 11 Discovery of potential collaboration networks from open knowledge sources ... Piedra, Nelson; Chicaiza, Janneth; Lopez-Vargas, Jorge. - : arXiv, 2017 BASE Show details 12 Using Linguistic Analysis to Translate Arabic Natural Language Queries to SPARQL ... AlAgha, Iyad. - : arXiv, 2015 BASE Show details 13 Replication and Generalization of PRECISE ... Minock, Michael; Everling, Nils. - : arXiv, 2015 BASE Show details 14 Querying with Łukasiewicz logic ... Aguzzoli, Stefano; Codara, Pietro; Flaminio, Tommaso. - : arXiv, 2015 BASE Show details 15 Mining Generalized Patterns from Large Databases using Ontologies ... Kwuida, Leonard; Missaoui, Rokia; Boumedjout, Lahcen. - : arXiv, 2009 BASE Show details

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