Blauwal3 Text
============
Orange add-on for text mining. It provides access to publicly available data,
like NY Times, Twitter and PubMed. Further, it provides tools for preprocessing,
constructing vector spaces (like bag-of-words, topic modeling and word2vec) and
visualizations like word cloud end geo map. All features can be combined with
powerful data mining techniques from the Orange data mining framework.
See [documentation](http://orange3-text.readthedocs.org/).
Features
--------
#### Access to data
* Load a corpus of text documents
* Access publicly available data (The Guardian, NY Times, Twitter, Wikipedia, PubMed)
#### Text analysis
* Preprocess corpus
* Generate bag of words
* Embed documents into vector space
* Perform sentiment analysis
* Detect emotions in tweets
* Discover topics in the text
* Compute document statistics
* Visualize frequent words in the word cloud
* Find words that enrich selected documents
Raw data
{
"_id": null,
"home_page": "https://github.com/biolab/orange3-text",
"name": "Blauwal3-Text",
"maintainer": null,
"docs_url": null,
"requires_python": null,
"maintainer_email": null,
"keywords": "orange3-text, data mining, orange3 add-on",
"author": "\u5927\u5723\u5b9e\u9a8c\u697c",
"author_email": "dashenglab@163.com",
"download_url": "https://files.pythonhosted.org/packages/d0/a8/9d952331227c5f324d735edbfa4773520126dde666cba99d7cd4172d0ff9/blauwal3_text-1.6.0.tar.gz",
"platform": null,
"description": "Blauwal3 Text\r\n============\r\n\r\nOrange add-on for text mining. It provides access to publicly available data,\r\nlike NY Times, Twitter and PubMed. Further, it provides tools for preprocessing,\r\nconstructing vector spaces (like bag-of-words, topic modeling and word2vec) and\r\nvisualizations like word cloud end geo map. All features can be combined with\r\npowerful data mining techniques from the Orange data mining framework.\r\n\r\nSee [documentation](http://orange3-text.readthedocs.org/).\r\n\r\nFeatures\r\n--------\r\n#### Access to data\r\n* Load a corpus of text documents\r\n* Access publicly available data (The Guardian, NY Times, Twitter, Wikipedia, PubMed)\r\n\r\n#### Text analysis\r\n* Preprocess corpus\r\n* Generate bag of words\r\n* Embed documents into vector space\r\n* Perform sentiment analysis\r\n* Detect emotions in tweets\r\n* Discover topics in the text\r\n* Compute document statistics\r\n* Visualize frequent words in the word cloud\r\n* Find words that enrich selected documents\r\n",
"bugtrack_url": null,
"license": null,
"summary": "\u7528\u4e8e\u6587\u672c\u6316\u6398\u7684\u84dd\u9cb8\u9644\u52a0\u7ec4\u4ef6\u3002",
"version": "1.6.0",
"project_urls": {
"Download": "https://github.com/biolab/orange3-text/tarball/1.16.0",
"Homepage": "https://github.com/biolab/orange3-text"
},
"split_keywords": [
"orange3-text",
" data mining",
" orange3 add-on"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "78b74c222327a1b8171039f49e3b972046d38b5a94078369475e89b0369bc779",
"md5": "92fc8f0d2f407f91444a966de4128d97",
"sha256": "65fa25b5467c13b753f30ea2fdf80f298d6d2b1e5c3bd5c5db7b25758c7e9d06"
},
"downloads": -1,
"filename": "Blauwal3_Text-1.6.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "92fc8f0d2f407f91444a966de4128d97",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": null,
"size": 20837832,
"upload_time": "2024-09-27T08:25:59",
"upload_time_iso_8601": "2024-09-27T08:25:59.205738Z",
"url": "https://files.pythonhosted.org/packages/78/b7/4c222327a1b8171039f49e3b972046d38b5a94078369475e89b0369bc779/Blauwal3_Text-1.6.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "d0a89d952331227c5f324d735edbfa4773520126dde666cba99d7cd4172d0ff9",
"md5": "b43e8c5039cf3b2c0cb5a3923246a846",
"sha256": "7798cf08b2fb8acb0a472f19a81f6df78c0e65ede3451f8d830fc656d9ea12ce"
},
"downloads": -1,
"filename": "blauwal3_text-1.6.0.tar.gz",
"has_sig": false,
"md5_digest": "b43e8c5039cf3b2c0cb5a3923246a846",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 30369030,
"upload_time": "2024-09-27T08:26:16",
"upload_time_iso_8601": "2024-09-27T08:26:16.110926Z",
"url": "https://files.pythonhosted.org/packages/d0/a8/9d952331227c5f324d735edbfa4773520126dde666cba99d7cd4172d0ff9/blauwal3_text-1.6.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-09-27 08:26:16",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "biolab",
"github_project": "orange3-text",
"travis_ci": false,
"coveralls": true,
"github_actions": true,
"requirements": [
{
"name": "anyqt",
"specs": []
},
{
"name": "beautifulsoup4",
"specs": []
},
{
"name": "biopython",
"specs": []
},
{
"name": "conllu",
"specs": []
},
{
"name": "docx2txt",
"specs": [
[
">=",
"0.6"
]
]
},
{
"name": "gensim",
"specs": [
[
">=",
"4.3.3"
]
]
},
{
"name": "httpx",
"specs": [
[
"!=",
"0.23.1"
]
]
},
{
"name": "langdetect",
"specs": []
},
{
"name": "lemmagen3",
"specs": []
},
{
"name": "nltk",
"specs": [
[
">=",
"3.9.1"
]
]
},
{
"name": "numpy",
"specs": []
},
{
"name": "odfpy",
"specs": [
[
">=",
"1.3.5"
]
]
},
{
"name": "Orange3",
"specs": [
[
">=",
"3.35.0"
]
]
},
{
"name": "orange-widget-base",
"specs": [
[
">=",
"4.20.0"
]
]
},
{
"name": "orange-canvas-core",
"specs": []
},
{
"name": "owlready2",
"specs": []
},
{
"name": "pandas",
"specs": []
},
{
"name": "pypdf",
"specs": []
},
{
"name": "pyqtgraph",
"specs": []
},
{
"name": "pyyaml",
"specs": []
},
{
"name": "requests",
"specs": []
},
{
"name": "scikit-learn",
"specs": []
},
{
"name": "scipy",
"specs": []
},
{
"name": "serverfiles",
"specs": []
},
{
"name": "simhash",
"specs": [
[
">=",
"1.11"
]
]
},
{
"name": "shapely",
"specs": [
[
">=",
"2.0"
]
]
},
{
"name": "six",
"specs": []
},
{
"name": "tweepy",
"specs": [
[
">=",
"4.0.0"
]
]
},
{
"name": "ufal.udpipe",
"specs": [
[
">=",
"1.2.0.3"
]
]
},
{
"name": "trimesh",
"specs": [
[
">=",
"3.9.8"
]
]
},
{
"name": "wikipedia",
"specs": []
},
{
"name": "yake",
"specs": []
}
],
"tox": true,
"lcname": "blauwal3-text"
}
JSON
