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HESML V1R5 JAVA SOFTWARE LIBRARY OF ONTOLOGY-BASED SEMANTIC SIMILARITY MEASURES AND INFORMATION CONTENT MODELS
- Lastra-Díaz, Juan J.
- Lara-Clares, Alicia
- Garcia-Serrano, Ana
WORD SIMILARITY BENCHMARKS OF RECENT WORD EMBEDDING MODELS AND ONTOLOGY-BASED SEMANTIC SIMILARITY MEASURES
- Lastra-Díaz, Juan J.
- Goikoetxea, Josu
- Hadj Taieb, Mohamed Ali
- Garcia-Serrano, Ana
- Ben Aouicha, Mohamed
- Agirre, Eneko
HESML V2R1 JAVA SOFTWARE LIBRARY OF SEMANTIC SIMILARITY MEASURES FOR THE BIOMEDICAL DOMAIN
- Lara-Clares, Alicia
- Lastra-Díaz, Juan J.
- Garcia-Serrano, Ana
REPRODUCIBLE EXPERIMENTS ON THE MASTER THESIS: AN EXPERIMENTAL SURVEY OF NAMED ENTITY RECOGNITION METHODS IN THE BIOMEDICAL DOMAIN
- Hennig, Sebastian
- Garcia-Serrano, Ana
REPRODUCIBLE EXPERIMENTS ON WORD AND SENTENCE SIMILARITY MEASURES FOR THE BIOMEDICAL DOMAIN
- Lara-Clares, Alicia
- Lastra-Díaz, Juan J.
- Garcia-Serrano, Ana
This dataset introduces a set of reproducibility resources with the aim of allowing the exact replication of the experiments introduced by our main paper, which is a reproducible experimental survey on biomedical sentence similarity with the following aims: (1) to elucidate the state of the art of the problem; (2) to solve some reproducibility problems preventing the evaluation of most of current methods; (3) to evaluate several unexplored sentence similarity methods; (4) to evaluate for the first time an unexplored benchmark, called Corpus-Transcriptional-Regulation (CTR); (5) to carry out a study on the impact of the pre-processing stages and Named Entity Recognition (NER) tools on the performance of the sentence similarity methods; and finally, (6) to bridge the lack of software and data reproducibility resources for methods and experiments in this line of research. This dataset sets a self-contained reproducibility platform which contains the Java source code and binaries of our main benchmark program, as well as a Docker image which allows the exact replication of our experiments in any software platform supported by Docker, such as all Linux-based operating systems, Windows or MacOS. Our benchmark program is distributed with the UMLS SNOMED-CT and MeSH ontologies by courtesy of the US National Library of Medicine (NLM), as well as all needed software components with the aim of making the setup process easier. Our Docker image provides an exact virtual replica of the machine in which we ran our experiments, thus removing the need to carry-out any tedious setup process, such as the setup of the Python virtual environments and other software components.
HESML library is freely distributed for any non-commercial purpose under a CC By-NC-SA-4.0 license, subject to the citing of the two mains HESML papers [17] as attribution requirement. However, HESML distribution also includes other datasets, databases or data files whose use require the attribution acknowledgement by any user of HEMSL. Thus, we urge to the HESML users to fulfill with licensing terms related to other resources distributed with the library as detailed in its companion release notes.
FORMAL CONCEPT ANALYSIS FOR TOPIC DETECTION: A CLUSTERING QUALITY EXPERIMENTAL ANALYSIS
- Castellanos, Angel
- Cigarrán, Juan
- Garcia-Serrano, Ana
REPRODUCIBILITY DATASET FOR A BENCHMARK OF BIOMEDICAL SEMANTIC MEASURES LIBRARIES
- Lastra-Díaz, Juan J.
- Lara-Clares, Alicia
- Garcia-Serrano, Ana