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attentionranklib

https://github.com/oeg-upm/attentionranklib

Science Score: 44.0%

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    CITATION.cff file
    Found CITATION.cff file
  • ✓
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    Found codemeta.json file
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    Found .zenodo.json file
  • ○
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    JOSS paper metadata
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    Scientific vocabulary similarity
    Low similarity (7.7%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: oeg-upm
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Size: 4.56 MB
Statistics
  • Stars: 1
  • Watchers: 6
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 3 years ago · Last pushed about 1 year ago
Metadata Files
Readme License Citation

README.md

AttentionRankLib

Repository to develop AttentionRank algorithm as library

Based on the work: https://github.com/hd10-iupui/AttentionRank

Install

Using Python 3.9

pip install -r requirements.txt

pip install -e .

``` python -m spacy download encorewebsm python -m spacy download escorenewssm

```

Execution

python main.py --dataset_name example --model_name_or_path PlanTL-GOB-ES/roberta-base-bne --model_type roberta --lang es --type_execution exec --k_value 15 Important: The dataset must be in this folder with any name and all documents must be inside another folder named docsutf8 Results will be provided inside the folder of the dataset in a folder named res+k_value

Docker run

For a fast run use the dockerfile and this two commands.

``` docker build -t attentionranklib .

```

docker run --rm -v ./example:/app/example attentionranklib --dataset_name example --model_name_or_path PlanTL-GOB-ES/roberta-base-bne --model_type roberta --lang es --type_execution exec --k_value 15

Acknowledgments

Para su desarrollo este código ha recibido financiación del proyecto INESData (Infraestructura para la INvestigación de ESpacios de DAtos distribuidos en UPM), un proyecto financiado en el contexto de la convocatoria UNICO I+D CLOUD del Ministerio para la Transformación Digital y de la Función Pública en el marco del PRTR financiado por Unión Europea (NextGenerationEU).

Paper Citation

bibtext @inproceedings{Calleja2024, author = {Pablo Calleja and Patricia Martín-Chozas and Elena Montiel-Ponsoda}, title = {Benchmark for Automatic Keyword Extraction in Spanish: Datasets and Methods}, booktitle = {Poster Proceedings of the 40th Annual Conference of the Spanish Association for Natural Language Processing 2024 (SEPLN-P 2024)}, series = {CEUR Workshop Proceedings}, volume = {3846}, pages = {132--141}, year = {2024}, publisher = {CEUR-WS.org}, address = {Valladolid, Spain}, month = {September 24-27}, urn = {urn:nbn:de:0074-3846-7}, url = {https://ceur-ws.org/Vol-3846/} }

Owner

  • Name: Ontology Engineering Group (UPM)
  • Login: oeg-upm
  • Kind: organization
  • Email: oeg-dev@delicias.dia.fi.upm.es
  • Location: Boadilla del Monte, Madrid, Spain

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "Si usas este código, por favor cita el siguiente artículo:"
authors:
  - name: "Pablo Calleja"
  - name: "Patricia Martín-Chozas"
  - name: "Elena Montiel-Ponsoda"
title: "Benchmark for Automatic Keyword Extraction in Spanish: Datasets and Methods"
booktitle: "Poster Proceedings of the 40th Annual Conference of the Spanish Association for Natural Language Processing 2024 (SEPLN-P 2024)"
series: "CEUR Workshop Proceedings"
volume: "3846"
pages: "132-141"
year: "2024"
publisher: "CEUR-WS.org"
conference: 
  name: "40th International Conference of the Spanish Society for Natural Language Processing (SEPLN 2024)"
  place: "Valladolid, Spain"
  date-start: "2024-09-24"
  date-end: "2024-09-27"
url: "https://ceur-ws.org/Vol-3846/"
identifiers:
  - type: "urn"
    value: "urn:nbn:de:0074-3846-7"
date-released: "2024-09-24"

GitHub Events

Total
  • Push event: 3
Last Year
  • Push event: 3

Dependencies

requirements.txt pypi
  • Babel ==2.11.0
  • CacheControl ==0.12.11
  • Cython ==0.29.33
  • Flask ==1.1.4
  • GDAL ==3.0.4
  • HeapDict ==1.0.1
  • Jinja2 ==2.11.3
  • Keras-Preprocessing ==1.1.2
  • LunarCalendar ==0.0.9
  • Markdown ==3.4.1
  • MarkupSafe ==2.0.1
  • Pillow ==7.1.2
  • PyDrive ==1.3.1
  • PyGObject ==3.36.0
  • PyMeeus ==0.5.12
  • PyOpenGL ==3.1.6
  • PySocks ==1.7.1
  • PyWavelets ==1.4.1
  • PyYAML ==6.0
  • Pygments ==2.6.1
  • SQLAlchemy ==1.4.46
  • Send2Trash ==1.8.0
  • Sphinx ==3.5.4
  • Werkzeug ==1.0.1
  • absl-py ==1.3.0
  • aeppl ==0.0.33
  • aesara ==2.7.9
  • aiohttp ==3.8.3
  • aiosignal ==1.3.1
  • alabaster ==0.7.12
  • albumentations ==1.2.1
  • altair ==4.2.0
  • appdirs ==1.4.4
  • arviz ==0.12.1
  • astor ==0.8.1
  • astropy ==4.3.1
  • astunparse ==1.6.3
  • async-timeout ==4.0.2
  • atari-py ==0.2.9
  • atomicwrites ==1.4.1
  • attrs ==22.2.0
  • audioread ==3.0.0
  • autograd ==1.5
  • backcall ==0.2.0
  • beautifulsoup4 ==4.6.3
  • bert-embedding ==1.0.1
  • bleach ==5.0.1
  • blis ==0.7.9
  • bokeh ==2.3.3
  • branca ==0.6.0
  • bs4 ==0.0.1
  • cachetools ==5.2.1
  • catalogue ==2.0.8
  • certifi ==2022.12.7
  • cffi ==1.15.1
  • cftime ==1.6.2
  • chardet ==4.0.0
  • charset-normalizer ==2.1.1
  • click ==7.1.2
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  • colorcet ==3.0.1
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  • community ==1.0.0b1
  • confection ==0.0.3
  • cons ==0.4.5
  • contextlib2 ==0.5.5
  • convertdate ==2.4.0
  • crashtest ==0.3.1
  • crcmod ==1.7
  • cufflinks ==0.17.3
  • cupy-cuda11x ==11.0.0
  • cvxopt ==1.3.0
  • cvxpy ==1.2.3
  • cycler ==0.11.0
  • cymem ==2.0.7
  • daft ==0.0.4
  • dask ==2022.2.1
  • datascience ==0.17.5
  • datasets ==2.8.0
  • db-dtypes ==1.0.5
  • dbus-python ==1.2.16
  • debugpy ==1.0.0
  • decorator ==4.4.2
  • defusedxml ==0.7.1
  • descartes ==1.1.0
  • dill ==0.3.6
  • distributed ==2022.2.1
  • dlib ==19.24.0
  • dm-tree ==0.1.8
  • dnspython ==2.2.1
  • docopt ==0.6.2
  • docutils ==0.16
  • dopamine-rl ==1.0.5
  • earthengine-api ==0.1.335
  • easydict ==1.10
  • ecos ==2.0.12
  • editdistance ==0.5.3
  • entrypoints ==0.4
  • ephem ==4.1.4
  • et-xmlfile ==1.1.0
  • etils ==1.0.0
  • etuples ==0.3.8
  • fa2 ==0.3.5
  • fastai ==2.7.10
  • fastcore ==1.5.27
  • fastdownload ==0.0.7
  • fastdtw ==0.3.4
  • fastjsonschema ==2.16.2
  • fastprogress ==1.0.3
  • fastrlock ==0.8.1
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  • filelock ==3.9.0
  • firebase-admin ==5.3.0
  • fix-yahoo-finance ==0.0.22
  • flatbuffers ==1.12
  • folium ==0.12.1.post1
  • frozenlist ==1.3.3
  • fsspec ==2022.11.0
  • future ==0.16.0
  • gast ==0.4.0
  • gdown ==4.4.0
  • gensim ==3.6.0
  • geographiclib ==1.52
  • geopy ==1.17.0
  • gin-config ==0.5.0
  • glob2 ==0.7
  • gluonnlp ==0.6.0
  • graphviz ==0.8.4
  • greenlet ==2.0.1
  • grpcio ==1.51.1
  • grpcio-status ==1.48.2
  • gspread ==3.4.2
  • gspread-dataframe ==3.0.8
  • gym ==0.25.2
  • gym-notices ==0.0.8
  • h5py ==3.1.0
  • hijri-converter ==2.2.4
  • holidays ==0.18
  • holoviews ==1.14.9
  • html5lib ==1.0.1
  • httpimport ==0.5.18
  • httplib2 ==0.17.4
  • httpstan ==4.6.1
  • huggingface-hub ==0.11.1
  • humanize ==0.5.1
  • hyperopt ==0.1.2
  • idna ==2.10
  • imageio ==2.9.0
  • imagesize ==1.4.1
  • imbalanced-learn ==0.8.1
  • imblearn ==0.0
  • imgaug ==0.4.0
  • importlib-metadata ==6.0.0
  • importlib-resources ==5.10.2
  • imutils ==0.5.4
  • inflect ==2.1.0
  • intel-openmp ==2023.0.0
  • intervaltree ==2.1.0
  • ipykernel ==5.3.4
  • ipython ==7.9.0
  • ipython-genutils ==0.2.0
  • ipython-sql ==0.3.9
  • ipywidgets ==7.7.1
  • itsdangerous ==1.1.0
  • jax ==0.3.25
  • jieba ==0.42.1
  • joblib ==1.2.0
  • jpeg4py ==0.1.4
  • jsonschema ==4.3.3
  • jupyter-client ==6.1.12
  • jupyter-console ==6.1.0
  • jupyter_core ==5.1.3
  • jupyterlab-widgets ==3.0.5
  • kaggle ==1.5.12
  • kapre ==0.3.7
  • keras ==2.9.0
  • keras-vis ==0.4.1
  • kiwisolver ==1.4.4
  • korean-lunar-calendar ==0.3.1
  • langcodes ==3.3.0
  • libclang ==15.0.6.1
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  • lmdb ==0.99
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  • logical-unification ==0.4.5
  • lxml ==4.9.2
  • marshmallow ==3.19.0
  • matplotlib ==3.2.2
  • matplotlib-venn ==0.11.7
  • miniKanren ==1.0.3
  • missingno ==0.5.1
  • mistune ==0.8.4
  • mizani ==0.7.3
  • mkl ==2019.0
  • mlxtend ==0.14.0
  • more-itertools ==9.0.0
  • moviepy ==0.2.3.5
  • mpmath ==1.2.1
  • msgpack ==1.0.4
  • multidict ==6.0.4
  • multipledispatch ==0.6.0
  • multiprocess ==0.70.14
  • multitasking ==0.0.11
  • murmurhash ==1.0.9
  • music21 ==5.5.0
  • mxnet ==1.4.0
  • natsort ==5.5.0
  • nbconvert ==5.6.1
  • nbformat ==5.7.1
  • netCDF4 ==1.6.2
  • networkx ==3.0
  • nibabel ==3.0.2
  • nltk ==3.7
  • notebook ==5.7.16
  • numba ==0.56.4
  • numexpr ==2.8.4
  • numpy ==1.14.6
  • oauth2client ==4.1.3
  • oauthlib ==3.2.2
  • okgrade ==0.4.3
  • opencv-contrib-python ==4.6.0.66
  • opencv-python ==4.6.0.66
  • opencv-python-headless ==4.7.0.68
  • openpyxl ==3.0.10
  • opt-einsum ==3.3.0
  • osqp ==0.6.2.post0
  • packaging ==21.3
  • palettable ==3.3.0
  • pandas ==1.3.5
  • pandas-datareader ==0.9.0
  • pandas-gbq ==0.17.9
  • pandas-profiling ==1.4.1
  • pandocfilters ==1.5.0
  • panel ==0.12.1
  • param ==1.12.3
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  • pastel ==0.2.1
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  • patsy ==0.5.3
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  • pexpect ==4.8.0
  • pickleshare ==0.7.5
  • pip-tools ==6.6.2
  • platformdirs ==2.6.2
  • plotly ==5.5.0
  • plotnine ==0.8.0
  • pluggy ==0.7.1
  • pooch ==1.6.0
  • portpicker ==1.3.9
  • prefetch-generator ==1.0.3
  • preshed ==3.0.8
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  • promise ==2.3
  • prompt-toolkit ==2.0.10
  • prophet ==1.1.1
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  • pydantic ==1.10.4
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  • pyparsing ==3.0.9
  • pyrsistent ==0.19.3
  • pysimdjson ==3.2.0
  • pystan ==3.3.0
  • pytest ==3.6.4
  • python-apt ==2.0.0
  • python-dateutil ==2.8.2
  • python-louvain ==0.16
  • python-slugify ==7.0.0
  • python-utils ==3.4.5
  • pytz ==2022.7
  • pyviz-comms ==2.2.1
  • pyzmq ==23.2.1
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  • qudida ==0.0.4
  • regex ==2022.6.2
  • requests ==2.25.1
  • requests-oauthlib ==1.3.1
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  • scipy ==1.7.3
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  • scs ==3.2.2
  • seaborn ==0.11.2
  • seqeval ==1.2.2
  • setuptools-git ==1.2
  • shapely ==2.0.0
  • six ==1.15.0
  • sklearn-pandas ==1.8.0
  • smart-open ==6.3.0
  • snowballstemmer ==2.2.0
  • sortedcontainers ==2.4.0
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  • sphinxcontrib.applehelp ==1.0.3
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  • tensorflow-datasets ==4.8.1
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  • torchtext ==0.14.1
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  • typing_extensions ==4.4.0
  • tzlocal ==1.5.1
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  • webargs ==8.2.0
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  • zict ==2.2.0
  • zipp ==3.11.0
setup.py pypi
  • List *
Dockerfile docker
  • python 3.9.6 build
requirements-torch.txt pypi