activity
20162023
most citedKnowledge Graphs in Manufacturing and Production: A Systematic Literature Review

152 citations · 254 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2023

Automatic Design of Semantic Similarity Ensembles Using Grammatical Evolution

Jorge Martinez-Gil

Semantic similarity measures are a key component in natural language processing tasks such as document analysis, requirement matching, and user input interpretation. However, the p…

cs.CL2023★ 1 cited

Context-Aware Semantic Similarity Measurement for Unsupervised Word Sense Disambiguation

Jorge Martinez-Gil

The issue of word sense ambiguity poses a significant challenge in natural language processing due to the scarcity of annotated data to feed machine learning models to face the cha…

cs.CL2023★ 15 cited

Optimizing Readability Using Genetic Algorithms

Jorge Martinez-Gil

This research presents ORUGA, a method that tries to automatically optimize the readability of any text in English. The core idea behind the method is that certain factors affect t…

cs.IR2021★ 55 cited

A Survey on Legal Question Answering Systems

Jorge Martinez-Gil

Many legal professionals think that the explosion of information about local, regional, national, and international legislation makes their practice more costly, time-consuming, an…

cs.AI2020★ 152 cited

Knowledge Graphs in Manufacturing and Production: A Systematic Literature Review

Georg Buchgeher, David Gabauer, Jorge Martinez-Gil +1

Knowledge graphs in manufacturing and production aim to make production lines more efficient and flexible with higher quality output. This makes knowledge graphs attractive for com…

cs.OH2016★ 31 cited

A Novel Approach for Learning How to Automatically Match Job Offers and Candidate Profiles

Jorge Martinez-Gil, Alejandra Lorena Paoletti, Mario Pichler

Automatic matching of job offers and job candidates is a major problem for a number of organizations and job applicants that if it were successfully addressed could have a positive…

cs.DB2016

SIFT: An Algorithm for Extracting Structural Information From Taxonomies

Jorge Martinez-Gil

In this work we present SIFT, a 3-step algorithm for the analysis of the structural information represented by means of a taxonomy. The major advantage of this algorithm is the cap…