Extract Relevant Keywords Conveyed in the Text

Gather and analyze large volumes of textual data from multiple sources and extract significant information with BytesView.

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What is Keyword Extraction?

Keyword extraction also known as keyword detection is a machine learning technique that can help you automate the identification and extraction of relevant information from unstructured text data.

Summarize the contents in textual data and key topics of discussion.

BytesView's efficient keyword extraction tool can analyze unstructured text including customer feedback, emails, surveys, social media posts, etc. Pre-define tags to identify topical content, business intelligence, customer opinions, and recurring tickets.

Build and train custom keyword extraction models with data specific to your organization and increase accuracy.

Keyword 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 Keyword Extraction Technical Specifications

Technical Specification of sentiment Analysis
Deployment Availability
BytesView Server
BytesView Cloud
Amazon Web Server
Plugins
Google Spreadsheet
Zendesk(Coming Soon)
Bindings
Curl,
Python,
Php,
Java,
Curl,
R,
Ruby,
C#,
Node.JS
Supported Languages
English
Industries
Specific Keyword Extraction Model Developed For
Customization
Customized solution as per your need

How can your Business Benefit From a Keyword Extraction tool?

Monitoring Social Media

Keyword extraction can give valuable insights of what people are saying about your business on social media. Finding keywords will allow you to monitor popular trends, perform market research, and track and monitor your competition in a more efficient manner.

Monitoring Social Media
Improving Customer Service

Improving Customer Service

What are your customers complaining about? And why? Keyword extraction allows your customer support teams to get an overview so that they can allocate their time for issues that requires urgent attention.

Enhanced Competitive Analysis

Keyword extraction helps in understanding the public opinion towards any issue and how it has changed over a period of time. It allows you to compare your product and services with your competition based on a particular topic.

Enhanced Competitive Analysis

How to access BytesView Keyword Extraction Tool?

Given below are the steps to access the BytesView keyword 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 keyword extraction models, go through the video.
access gender detection

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

build custom sentiment analysis

Now train custom keyword 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 keyword 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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