DKPro Core
CoreNLP
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DKPro Core | CoreNLP | |
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0 | 11 | |
196 | 9,420 | |
-0.5% | 0.9% | |
6.0 | 9.3 | |
17 days ago | 8 days ago | |
Java | Java | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 only |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
DKPro Core
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Tracking mentions began in Dec 2020.
CoreNLP
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One does not simply "create a visualization" from unstructured data!
If your looking at spacy have a look at Apache OpenNLP and Core NLP.
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Has anyone here ever used the seaNMF model for short text topic modeling, and be willing to help me get started with it?
Tokenize with NLTK, SpaCy or CoreNLP
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How to use CoreNLP with a large corpus(14.7 GB)?
If you need further assistance, you will be better off making an issue on their github: https://github.com/stanfordnlp/CoreNLP
It should not take nearly that long. However, again I must recommend you take this conversation to github
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A comparison of libraries for named entity recognition
If you need NER, there’s no need to implement it yourself. There are several popular libraries that can do this for you nowadays. Five of these libraries, Stanford CoreNLP, NLTK, OpenNLP, SpaCy, and GATE, were already mentioned in the title.
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[D] Java vs Python for Machine learning
To give a contrasting perspective, I think the Java ecosystem is much better suited for many data science tasks, and has a growing and well-maintained set of libraries for general purpose machine learning. I won't list them all, but TF-Java, DJL et al. have implementations of many modern architectures and there are a number of excellent libraries (CoreNLP, Lucene et al.) for working with text.
What are some alternatives?
Apache OpenNLP - Apache OpenNLP
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
Mallet - MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text.
Deep Java Library (DJL) - An Engine-Agnostic Deep Learning Framework in Java
CogCompNLP - CogComp's Natural Language Processing Libraries and Demos: Modules include lemmatizer, ner, pos, prep-srl, quantifier, question type, relation-extraction, similarity, temporal normalizer, tokenizer, transliteration, verb-sense, and more.
Apache Solr - Apache Lucene and Solr open-source search software
java - Java bindings for TensorFlow
BotLibre - An open platform for artificial intelligence, chat bots, virtual agents, social media automation, and live chat automation.
SeaNMF - Short Text Topic Modeling