Apache Solr
CoreNLP
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Apache Solr | CoreNLP | |
---|---|---|
31 | 11 | |
4,365 | 9,460 | |
0.0% | 1.0% | |
0.0 | 9.1 | |
2 months ago | 11 days ago | |
Java | Java | |
Apache License 2.0 | GNU General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
Apache Solr
- Iniciando no Elasticsearch: Conceitos básicos
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YaCy, a distributed Web Search Engine, based on a peer-to-peer network
There are already many project about search:
- https://www.marginalia.nu/
- https://searchmysite.net/
- https://lucene.apache.org/
- elastic search
- https://presearch.com/
- https://stract.com/
- https://wiby.me/
I think that all project are fun. I would like to see one succeeding at reaching mainstream level of attention.
I have also been gathering links meta data for some time. Maybe I will use them to feed any eventual self hosted search engine, or language model, if I decide to experiment with that.
- domains for seed https://github.com/rumca-js/Internet-Places-Database
- bookmarks seed https://github.com/rumca-js/RSS-Link-Database
- links for year https://github.com/rumca-js/RSS-Link-Database-2024
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Getting started with Elasticsearch + Python
Elasticsearch is based on Lucene and is used by various companies and developers across the world to build custom search solutions.
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Tools to use to query and index data?
elastic search is kinda heavyweight infra for a small project. Its built on top of apache lucene (https://lucene.apache.org), which you can use directly.
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Top metrics for Elasticsearch monitoring with Prometheus
Elasticsearch is based on Lucene, which is built in Java. This means that monitoring the Java Virtual Machine (JVM) memory is crucial to understand the current usage of the whole system.
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Cross data type search that wasn’t supported well using Elasticsearch
Apache Lucene which seems to have a lot more features than Elasticsearch
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How to find closest keyphrase match in text?
Generally with term vectors and a tf-idf index. Lucene is a good starting place to help.
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Java Library to perform string search
try elasticsearch or solr, behind the scenes they both use https://lucene.apache.org/ if you don't want basically a full nosql database service, but I'd just slap solr up and call it a day.
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Top 8 Open-Source Observability & Testing Tools
OpenSearch is an open-source database to ingest, search, visualize, and analyze data. It’s built on top of Apache Lucerce, a FOSS library for indexing and search, which OpenSearch leverages for more advanced analytics capabilities, like anomaly detection, machine learning, full-text search, and more.
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grep like search with preprocessing
Lucene is the thing you think you need. Elastic Search is a nice wrapper for it. But these are Java, so maybe you want Sphinx Search (C++) or MeiliSearch (Rust).
CoreNLP
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How does "Reclaim.ai" use AI for smart rescheduling?
The Stanford CoreNLP Model
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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)?
It should not take nearly that long. However, again I must recommend you take this conversation to github
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What universities are hubs for reinforcement learning research?
Stanford has a great program and the Stanford NLP Group maintains CoreNLP which I have used before.
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POS-Tagger for declension of German words in Java?
So why not use the Stanford CoreNLP library?
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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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Making my own AI assistant
Check something like this out to start: https://stanfordnlp.github.io/CoreNLP/
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Good tutorials for PyTorch?
You don't actually even need to learn how to do deep learning if you're doing something fairly basic, which it sounds like you are. There are a lot of good tools you can use basically straight out of the box for something like this. Check out https://huggingface.co/course/chapter1, https://course.spacy.io/en/, https://guide.allennlp.org/ and https://www.nltk.org/book/. If java's more your thing, add https://stanfordnlp.github.io/CoreNLP/ to the list.
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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?
OpenSearch - 🔎 Open source distributed and RESTful search engine.
Apache OpenNLP - Apache OpenNLP
Typesense - Open Source alternative to Algolia + Pinecone and an Easier-to-Use alternative to ElasticSearch ⚡ 🔍 ✨ Fast, typo tolerant, in-memory fuzzy Search Engine for building delightful search experiences
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
MeiliSearch - A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
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.
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
Deep Java Library (DJL) - An Engine-Agnostic Deep Learning Framework in Java
loki - Like Prometheus, but for logs.
DKPro Core - Collection of software components for natural language processing (NLP) based on the Apache UIMA framework.
Apache Lucene - Apache Lucene.NET
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.