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The method uses a greedy filtering approach based on various univariate measures of feature relevance and it is very fast in practice. Also, our feature ...
In this paper, we propose and evaluate some new unsupervised language modeling approaches to determine the membership level of a candidate answer, a named ...
A Feature Induction Algorithm with Application to Named Entity Disambiguation. Author: Iva Mechkunova. Date Published: September 09, 2013.
1 Introduction · 2 Methods. 2.1 Feature ranking and filtering; 2.2 Induction (generating conjunctions); 2.3 Complexity of the algorithm; 2.4 Model training and ...
Named Entity Disambiguation (NED) is the task of linking a named-entity ... A Feature Induction Algorithm with Application to Named Entity Disambiguation.
A Feature Induction Algorithm with Application to Named Entity Disambiguation · no code implementations • RANLP 2013 • Laura Tolo{\c{s}}i, Valentin Zhikov ...
[simulated annealing] Simulated annealing (SA) is a generic probabilistic metaheuristic for the global optimization problem of locating a good approximation to ...
Jun 10, 2024 · Named Entity Disambiguation (NED) is the process of resolving ambiguities in named entities by linking them to their correct references in a knowledge base.
Missing: Induction | Show results with:Induction
Sep 3, 2024 · The paper explores Semantic Table Interpretation, addressing the challenges of Entity Retrieval and Entity Disambiguation in the context of Knowledge Graphs ( ...
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Dec 15, 2020 · This method of congruence using 100d embeddings improves predictive accuracy of named entity disambiguation by a range of 2.4–3.7% depending ...