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توضیحات

Semantic Textual Similarity and Dialogue System package for Python

ویژگی	مقدار
سیستم عامل	-
نام فایل	ASAPPpy-0.2b1
نام	ASAPPpy
نسخه کتابخانه	0.2b1
نگهدارنده	[]
ایمیل نگهدارنده	[]
نویسنده	José Santos
ایمیل نویسنده	santos@student.dei.uc.pt
آدرس صفحه اصلی	-
آدرس اینترنتی	https://pypi.org/project/ASAPPpy/
مجوز	MIT License

## ASAPPpy ASAPPpy is a Python package for developing models to compute the Semantic Textual Similarity (STS) between texts in Portuguese. These models follow a supervised learning approach to learn an STS function from annotated sentence pairs, considering a variety of lexical, syntactic, semantic and distributional features. ASAPPpy can also be used to develop STS based dialogue agents and deploy them to Slack. ### Development If you want to contribute to this project, please follow the [Google Python Style Guide](https://google.github.io/styleguide/pyguide.html). ### Installation Before getting started, verify that <b>pip >= 20.3.3</b>. If not, update it with this command: ```bash pip install --upgrade pip ``` To install the latest version of ASAPPpy use the following command: ```bash pip install ASAPPpy ``` After finishing the installation, you might need to download the word embeddings models. Given that they were obtained from various sources, we collected them and they can be downloaded at once by running the Python interpreter in your terminal followed by these commands: ```python import ASAPPpy ASAPPpy.download() ``` Finally, if you have never used [spaCy](https://spacy.io) before and you want to use the dependency parsing features, you will need to run the next command in the terminal: ```bash python -m spacy download pt_core_news_sm ``` Alternatively, you can check the latest version of ASAPPpy using this command: ```bash git clone https://github.com/ZPedroP/ASAPPpy.git ``` ### Project History ASAP(P) is the name of a collection of systems developed by the [Natural Language Processing group](http://nlp.dei.uc.pt) at [CISUC](https://www.cisuc.uc.pt/home) for computing STS based on a regression method and a set of lexical, syntactic, semantic and distributional features extracted from text. It was used to participate in several STS evaluation tasks, for English and Portuguese, but was only recently integrated into two single independent frameworks: ASAPPpy (available here), in Python, and ASAPPj, in Java. ### Help and Support #### Documentation Coming soon... #### Communication If you have any questions feel free to open a new issue and we will respond as soon as possible. #### Citation When [citing ASAPPpy in academic papers and theses](http://ceur-ws.org/Vol-2583/2_ASAPPpy.pdf), please use the following BibTeX entry: @inproceedings{santos_etal:assin2020, title = {ASAPPpy: a Python Framework for Portuguese STS}, author = {José Santos and Ana Alves and Hugo {Gonçalo Oliveira}}, url = {http://ceur-ws.org/Vol-2583/2_ASAPPpy.pdf}, year = {2020}, date = {2020-01-01}, booktitle = {Proceedings of the ASSIN 2 Shared Task: Evaluating Semantic Textual Similarity and Textual Entailment in Portuguese}, volume = {2583}, pages = {14--26}, publisher = {CEUR-WS.org}, series = {CEUR Workshop Proceedings}, keywords = {aia, asap, sts}, pubstate = {published}, tppubtype = {inproceedings} }

نیازمندی

مقدار	نام
==49.6.0	setuptools
==0.7.0	imbalanced-learn
>=0.22.2	scikit-learn
>=1.1.1	pandas
-	requests
==2.1.0	slackclient
==2.1.0	slackeventsapi
==3.4.5	nltk
==2.2.5	NLPyPort
-	spacy
-	gensim
-	joblib
-	num2words
-	Whoosh
-	Keras
-	tensorflow
-	cufflinks
-	matplotlib
-	seaborn

زبان مورد نیاز

مقدار	نام
>=3.6.1	Python

نحوه نصب

نصب پکیج whl ASAPPpy-0.2b1:

pip install ASAPPpy-0.2b1.whl

نصب پکیج tar.gz ASAPPpy-0.2b1:

pip install ASAPPpy-0.2b1.tar.gz