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Average Ratings 0 Ratings
Description
Komprehend AI offers an extensive range of document classification and NLP APIs designed specifically for software developers. Our advanced NLP models leverage a vast dataset of over a billion documents, achieving top-notch accuracy in various common NLP applications, including sentiment analysis and emotion detection. Explore our free demo today to experience the effectiveness of our Text Analysis API firsthand. It consistently delivers high accuracy in real-world scenarios, extracting valuable insights from open-ended text data. Compatible with a wide range of industries, from finance to healthcare, it also supports private cloud implementations using Docker containers or on-premise deployments, ensuring your data remains secure. By adhering to GDPR compliance guidelines meticulously, we prioritize the protection of your information. Gain insights into the social sentiment surrounding your brand, product, or service by actively monitoring online discussions. Sentiment analysis involves the contextual examination of text to identify and extract subjective insights from the material, thereby enhancing your understanding of audience perceptions. Additionally, our tools allow for seamless integration into existing workflows, making it easier for developers to harness the power of NLP.
Description
TextBlob is a Python library designed for handling textual data, providing an intuitive API to carry out various natural language processing functions such as part-of-speech tagging, sentiment analysis, noun phrase extraction, and classification tasks. Built on the foundations of NLTK and Pattern, it integrates seamlessly with both libraries. Notable features encompass tokenization (the division of text into words and sentences), frequency analysis of words and phrases, parsing capabilities, n-grams, and word inflection (both pluralization and singularization), alongside lemmatization, spelling correction, and integration with WordNet. TextBlob is compatible with Python versions 2.7 and higher, as well as 3.5 and above. The library is actively maintained on GitHub and is released under the MIT License. For users seeking guidance, thorough documentation is readily accessible, including a quick start guide and a variety of tutorials to facilitate the implementation of different NLP tasks. This rich resource equips developers with the tools necessary to enhance their text processing capabilities.
API Access
Has API
Yes
API Access
Has API
Yes
Pricing Details
$79 per month
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Komprehend
Country
India
Website
komprehend.io
Vendor Details
Company Name
TextBlob
Country
United States
Website
textblob.readthedocs.io/en/dev/
Product Features
Emotion Recognition
Facial Emotions
No
Facial Expression Analysis
No
Machine Learning
No
Photo Emotions
No
Speech Emotions
No
Video Emotions
No
Written Text Emotions
No
Natural Language Processing
Co-Reference Resolution
No
In-Database Text Analytics
No
Named Entity Recognition
No
Natural Language Generation (NLG)
No
Open Source Integrations
No
Parsing
No
Part-of-Speech Tagging
No
Sentence Segmentation
No
Stemming/Lemmatization
No
Tokenization
No
Text Mining
Boolean Queries
No
Document Filtering
No
Graphical Data Presentation
No
Language Detection
No
Predictive Modeling
No
Sentiment Analysis
No
Summarization
No
Tagging
No
Taxonomy Classification
No
Text Analysis
No
Topic Clustering
No
Product Features
Natural Language Processing
Co-Reference Resolution
No
In-Database Text Analytics
No
Named Entity Recognition
No
Natural Language Generation (NLG)
No
Open Source Integrations
No
Parsing
No
Part-of-Speech Tagging
No
Sentence Segmentation
No
Stemming/Lemmatization
No
Tokenization
No