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Subject: Computer and Information Science

61 to 70 of 85 Results

Prediction and Comparative Analysis of CTCF Binding Sites based on a First Principle Approach [Research Data] Mar 7, 2022 - Theoretical Physics Li, Kunhe; Oiwa, Nestor Norio; Cordeiro, Claudette E.; Heermann, Dieter W., 2022, "Prediction and Comparative Analysis of CTCF Binding Sites based on a First Principle Approach [Research Data]", https://doi.org/10.11588/data/RDISCE, heiDATA, V1 The file contains the CTCF-DNA binding sites for complete genome of Homo sapiens (human), Mus musculus (mouse), Sus scrofa (pig), Capra hircus (goat), Aedes aegypti (dengue and yellow fever mosquito) and Drosophila melanogaster (fruit fly) using electronic nucleotide alignment. T...
Real-World PP Attachment Disambiguation Dataset Nov 13, 2023 - Neural Techniques for German Dependency Parsing Do, Bich-Ngoc; Rehbein, Ines, 2023, "Real-World PP Attachment Disambiguation Dataset", https://doi.org/10.11588/data/NB46XR, heiDATA, V1 This resource contains a German dataset for real-world PP attachment disambiguation. The creation, analysis and experiment results of the dataset are described in the paper: Do and Rehbein (2020). "Parsers Know Best: German PP Attachment Revisited"
Rektorbuch RA 653 - University of Heidelberg Apr 16, 2015 - IWR Computer Graphics Krömker, Susanne; Mara, Hubert, 2015, "Rektorbuch RA 653 - University of Heidelberg", https://doi.org/10.11588/data/10054, heiDATA, V1 Capturing the Heidelberg University's sealings with a 3D-scanner provides new visualizations and virtual restoration possibilities for the partially preserved damaged objects. High-resolution 3D-models are analyzed due to their surface features, which cannot be documented with ph...
Selectional Preference Embeddings (EMNLP 2017) Jan 31, 2019 - AIPHES Heinzerling, Benjamin, 2019, "Selectional Preference Embeddings (EMNLP 2017)", https://doi.org/10.11588/data/FJQ4XL, heiDATA, V1 Joint embeddings of selectional preferences, words, and fine-grained entity types. The vocabulary consists of: verbs and their dependency relation separated by "@", e.g. "sink@nsubj" or "elect@dobj" words and short noun phrases, e.g. "Titanic" fine-grained entity types using the...
Sensor-Based Measurements in Paraplegia: Classified References from a Systematic Review Jan 4, 2020 - Medical Informatics Benning, Nils-Hendrik; Hagen, Niclas; Knaup, Petra, 2020, "Sensor-Based Measurements in Paraplegia: Classified References from a Systematic Review", https://doi.org/10.11588/data/JRVJGN, heiDATA, V1, UNF:6:f63Fk7qwB3+Tc3vOEqFdnA== [fileUNF] This dataset contains the results (publication references) of the systematic review "Current Use of Sensor-Based Measurements for Paraplegics", presented at MIE 2020, Geneva.
Sentiment Compound Data (DE) Sep 5, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo) Wiegand, Michael; Bocionek, Christine; Ruppenhofer, Josef, 2019, "Sentiment Compound Data (DE)", https://doi.org/10.11588/data/LSTRK3, heiDATA, V1 This dataset contains gold standards that are required for building a classifier that automatically extracts opinion (noun) compounds.
Sentiment View Lexicon (EN) Sep 5, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo) Wiegand, Michael; Ruppenhofer, Josef; Schulder, Marc, 2019, "Sentiment View Lexicon (EN)", https://doi.org/10.11588/data/2JK48O, heiDATA, V1 This gold standard contains sentiment expressions (verbs, nouns and adjectives) that have been annotated according to their (prior) sentiment view. Each sentiment expression is labelled either as actor or speaker view.
SimTool-SynBench Oct 25, 2023 - Data Analysis and Modeling in Medicine Marvin Kinz, 2023, "SimTool-SynBench", https://doi.org/10.11588/data/R9IKCF, heiDATA, V2 The SimTool is a toolset to simulate soft tissue deformation during resection surgery. The proposed toolset is an assimilation of 3D packages in Python and Unreal Engine 4 (UE4) with Nvidia Flex integration, which make it possible to adapt the dataset for more applications. The S...
Source code and data for the PhD Thesis "Learning Neural Graph Representations in Non-Euclidean Geometries" Apr 18, 2023 - PhD related material - Faculty of Modern Languages Lopez, Federico, 2023, "Source code and data for the PhD Thesis "Learning Neural Graph Representations in Non-Euclidean Geometries"", https://doi.org/10.11588/data/KOAMK4, heiDATA, V1 This dataset contains source code and data used in the PhD thesis "Learning Neural Graph Representations in Non-Euclidean Geometries". The dataset is split into four repositories: figet: Source code to run experiments for chapter 6 "Constructing and Exploiting Hierarchical Graphs...
Source code and data for the PhD Thesis "Metrics of Graph-Based Meaning Representations with Applications from Parsing Evaluation to Explainable NLG Evaluation and Semantic Search" Jan 17, 2024 - Natural Language Processing Group Opitz, Juri Alexander, 2024, "Source code and data for the PhD Thesis "Metrics of Graph-Based Meaning Representations with Applications from Parsing Evaluation to Explainable NLG Evaluation and Semantic Search"", https://doi.org/10.11588/data/RAS7U7, heiDATA, V1 This dataset contains source code and data used in the PhD thesis "Metrics of Graph-Based Meaning Representations with Applications from Parsing Evaluation to Explainable NLG Evaluation and Semantic Search". The dataset is split into five repositories: S3BERT: Source code to run...

Prediction and Comparative Analysis of CTCF Binding Sites based on a First Principle Approach [Research Data]

Mar 7, 2022 - Theoretical Physics

Li, Kunhe; Oiwa, Nestor Norio; Cordeiro, Claudette E.; Heermann, Dieter W., 2022, "Prediction and Comparative Analysis of CTCF Binding Sites based on a First Principle Approach [Research Data]", https://doi.org/10.11588/data/RDISCE, heiDATA, V1

The file contains the CTCF-DNA binding sites for complete genome of Homo sapiens (human), Mus musculus (mouse), Sus scrofa (pig), Capra hircus (goat), Aedes aegypti (dengue and yellow fever mosquito) and Drosophila melanogaster (fruit fly) using electronic nucleotide alignment. T...

Real-World PP Attachment Disambiguation Dataset

Nov 13, 2023 - Neural Techniques for German Dependency Parsing

Do, Bich-Ngoc; Rehbein, Ines, 2023, "Real-World PP Attachment Disambiguation Dataset", https://doi.org/10.11588/data/NB46XR, heiDATA, V1

This resource contains a German dataset for real-world PP attachment disambiguation. The creation, analysis and experiment results of the dataset are described in the paper: Do and Rehbein (2020). "Parsers Know Best: German PP Attachment Revisited"

Rektorbuch RA 653 - University of Heidelberg

Apr 16, 2015 - IWR Computer Graphics

Krömker, Susanne; Mara, Hubert, 2015, "Rektorbuch RA 653 - University of Heidelberg", https://doi.org/10.11588/data/10054, heiDATA, V1

Capturing the Heidelberg University's sealings with a 3D-scanner provides new visualizations and virtual restoration possibilities for the partially preserved damaged objects. High-resolution 3D-models are analyzed due to their surface features, which cannot be documented with ph...

Selectional Preference Embeddings (EMNLP 2017)

Jan 31, 2019 - AIPHES

Heinzerling, Benjamin, 2019, "Selectional Preference Embeddings (EMNLP 2017)", https://doi.org/10.11588/data/FJQ4XL, heiDATA, V1

Joint embeddings of selectional preferences, words, and fine-grained entity types. The vocabulary consists of: verbs and their dependency relation separated by "@", e.g. "sink@nsubj" or "elect@dobj" words and short noun phrases, e.g. "Titanic" fine-grained entity types using the...

Sensor-Based Measurements in Paraplegia: Classified References from a Systematic Review

Jan 4, 2020 - Medical Informatics

Benning, Nils-Hendrik; Hagen, Niclas; Knaup, Petra, 2020, "Sensor-Based Measurements in Paraplegia: Classified References from a Systematic Review", https://doi.org/10.11588/data/JRVJGN, heiDATA, V1, UNF:6:f63Fk7qwB3+Tc3vOEqFdnA== [fileUNF]

This dataset contains the results (publication references) of the systematic review "Current Use of Sensor-Based Measurements for Paraplegics", presented at MIE 2020, Geneva.

Sentiment Compound Data (DE)

Sep 5, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)

Wiegand, Michael; Bocionek, Christine; Ruppenhofer, Josef, 2019, "Sentiment Compound Data (DE)", https://doi.org/10.11588/data/LSTRK3, heiDATA, V1

This dataset contains gold standards that are required for building a classifier that automatically extracts opinion (noun) compounds.

Sentiment View Lexicon (EN)

Sep 5, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)

Wiegand, Michael; Ruppenhofer, Josef; Schulder, Marc, 2019, "Sentiment View Lexicon (EN)", https://doi.org/10.11588/data/2JK48O, heiDATA, V1

This gold standard contains sentiment expressions (verbs, nouns and adjectives) that have been annotated according to their (prior) sentiment view. Each sentiment expression is labelled either as actor or speaker view.

SimTool-SynBench

Oct 25, 2023 - Data Analysis and Modeling in Medicine

Marvin Kinz, 2023, "SimTool-SynBench", https://doi.org/10.11588/data/R9IKCF, heiDATA, V2

The SimTool is a toolset to simulate soft tissue deformation during resection surgery. The proposed toolset is an assimilation of 3D packages in Python and Unreal Engine 4 (UE4) with Nvidia Flex integration, which make it possible to adapt the dataset for more applications. The S...

Source code and data for the PhD Thesis "Learning Neural Graph Representations in Non-Euclidean Geometries"

Apr 18, 2023 - PhD related material - Faculty of Modern Languages

Lopez, Federico, 2023, "Source code and data for the PhD Thesis "Learning Neural Graph Representations in Non-Euclidean Geometries"", https://doi.org/10.11588/data/KOAMK4, heiDATA, V1

This dataset contains source code and data used in the PhD thesis "Learning Neural Graph Representations in Non-Euclidean Geometries". The dataset is split into four repositories: figet: Source code to run experiments for chapter 6 "Constructing and Exploiting Hierarchical Graphs...

Source code and data for the PhD Thesis "Metrics of Graph-Based Meaning Representations with Applications from Parsing Evaluation to Explainable NLG Evaluation and Semantic Search"

Jan 17, 2024 - Natural Language Processing Group

Opitz, Juri Alexander, 2024, "Source code and data for the PhD Thesis "Metrics of Graph-Based Meaning Representations with Applications from Parsing Evaluation to Explainable NLG Evaluation and Semantic Search"", https://doi.org/10.11588/data/RAS7U7, heiDATA, V1

This dataset contains source code and data used in the PhD thesis "Metrics of Graph-Based Meaning Representations with Applications from Parsing Evaluation to Explainable NLG Evaluation and Semantic Search". The dataset is split into five repositories: S3BERT: Source code to run...

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