Keatext VS spaCy
Compare Keatext VS spaCy and see what are their differences
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Keatext
Chattermill
RapidMiner
Farrago
monkeylearn
Tibco Data Science
Stratifyd
Customer Thermometer
spaCy
Amazon Comprehend
Google Cloud Natural Language API
FuzzyWuzzy
Microsoft Bing Spell Check API
NLTK
OpenNLP
monkeylearn
Keatext is a CX analytics solution that provides AI-based predictive recommendations to improve customer satisfaction.
Get recommendations from your customer responses like reviews, open ended surveys, and contact center tickets to support data-driven decisions and be a more customer-centric organization.
Bring forward decisions with impact: Zero in on opportunities to increase ROI and identify strengths and weaknesses from your customer data
Monitor every stage of the customer journey: Build a complete view of what drives customer satisfaction and discontent
Automate how you generate customer intelligence: Uncover customer insights you can act on without any heavy lifting
Key features
The application is cloud-based and requires no advanced setup or training to start getting insights.
Keatext is trusted by companies in over 10 industries including Lenovo, Intuit, and Intelcom. By using the platform, clients not only improve their customer experience KPIs but help their organization become more customer-centric.
KeatextNo features have been listed yet.
Based on our record, spaCy seems to be more popular. It has been mentiond 58 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Hi Community, In this article, I will demonstrate below steps to create your own chatbot by using spaCy (spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython):. - Source: dev.to / about 1 month ago
SpaCy: An open-source library providing tools for advanced NLP tasks like tokenization, entity recognition, and part-of-speech tagging. Source: 5 months ago
In this article, I'm going to walk through a sentiment analysis project from start to finish, using open-source Amazon product reviews. However, using the same approach, you can easily implement mass sentiment analysis on your own products. We'll explore an approach to sentiment analysis with one of the most popular Python NLP packages: spaCy. - Source: dev.to / 7 months ago
Spacy [0] is a state-of-art / easy-to-use NLP library from the pre-LLM era. This post is the Spacy founder's thoughts on how to integrate LLMs with the kind of problems that "traditional" NLP is used for right now. It's an advertisement for Prodigy [1], their paid tool for using LLMs to assist data labeling. That said, I think I largely agree with the premise, and it's worth reading the entire post. The steps... - Source: Hacker News / 8 months ago
I chose spacy. Although it's not state of the art, it's very well established and stable. Source: 10 months ago
Chattermill - Extract actionable insights from customer feedback using deep learning
Amazon Comprehend - Discover insights and relationships in text
RapidMiner - RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.
Google Cloud Natural Language API - Natural language API using Google machine learning
Farrago - Intuitive soundboard app to quickly play sound bites, audio effects, and music clips.
FuzzyWuzzy - FuzzyWuzzy is a Fuzzy String Matching in Python that uses Levenshtein Distance to calculate the differences between sequences.