Identify Features Conveyed in the Text

Use AI to automatically detect and classify important subsets of features from unstructured text data from any industry.

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What is Feature Extraction?

Feature extraction is the process of identifying and extracting product aspects from extensive volumes of textual data. Dissect comments, reviews, social media posts, opinions, news, etc. to identify features conveyed in the text.

Use feature extraction to cut through the noise and convert research data into game-changing insights.

BytesView's advanced feature extraction solution can analyze large volumes of text data and detect features along with related insights. Compare various products to examine how similar they are.

Perform market research or compare your product features with your competitors.

Feature Extraction Demo

Result

Positive
Neutral
Negative

Result

Accuracy

Topic Label

Result

News

Feedback

Promotion

Query

Spam

Result

Relatedness

Result

Angry

Fear

Happy

Sad

Love

Neutral

Result

Result

Result

BytesView Feature Extraction Technical Specifications

Technical Specification of sentiment Analysis
Deployment Availability
BytesView Server
BytesView Cloud
Amazon Web Server
Plugins
Google Spreadsheet
Zendesk
Zapier
Bindings
Curl,
Python,
Php,
Java,
Curl,
R,
Ruby,
C#,
Node.JS
Supported Languages
English,
Spanish,
Arabic,
French,
Persian,
Japanese,
(Add Support for more than 30 language)
Industries
Specific Feature Extraction Model Developed For
Customization
Customized solution as per your need

How can your Business Benefit From a Feature Extraction tool?

Feature Detection

Automate identifying and extracting features from large volumes of text data and create a summary of all unique features or a combination of features with our text extraction solution.

Feature Detection
Business Intelligence

Business Intelligence

Creating a product and hoping that consumers will like it is no longer an option. Brands and marketers need to understand the needs of their target audience. Use text extraction to gain valuable insights and create products with a compelling set of features.

Feature Identification

Create different groups of features by clustering similar or related features. Identify new product features or new segments of customers and develop more personalized and appealing products with text extraction.

Feature Identification

How to access BytesView Feature Extraction Tool?

Given below are the steps to access the BytesView feature extraction API. You can either gather the data by yourself in an excel/CSV format or ask us to do so.

  • Gather pieces of text and documents from multiple sources
  • Compile the gathered text data in an Excel/CSV file or Google spreadsheet
  • Install the BytesView plugins on Google spreadsheet and open the add-ons tab to locate it.
  • Create a demo account or Purchase a subscription plan that suits your requirements and get an API key.
  • Paste the given API key on the BytesView plugin to activate it
  • Select the cells you want to analyze and the machine learning model you want to use. Click run to start analyzing your data.
  • For more information on feature extraction models, go through the video.
access gender detection

Now build and train custom Feature Extraction Models as per your need

build custom sentiment analysis

Now train custom feature extraction models with data related to your organization to further increase accuracy of the output.

  • Collect the data you want to analyze and export them as a CSV or Excel file. Use a web scraping tool or let us do it for you.
  • Go on the BytesView dashboard and click on “create a model” and chose between a classifier or an extraction model.
  • Click on extractor and then select feature extraction model.
  • Import your data and select which column you want to analyze if there is more than one.
  • Tag relevant text that appears to train the feature extraction model. The model will begin making its own conclusions after a few tags.
  • Name and Test your model to see how it is working.
  • Once your model is trained, you can upload the whole data set to get results.

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