Page Ranker Tool
Extracts keywords from social channels, document repositories helps to define meta data tags and increases the SEO rank.
Business Problem
Customer wanted to improve the product page site visibility and rank of the site.
Unable to reach out to relevant users. Search result didn’t show the details relevant to Product.
Solution
This solution leverage the Machine Learning and Deep learning techniques to understand consumer preferences while they search for content.
- Fetch data from social media channel
- Preprocess data (Remove hyperlinks, emails, stop words)
- Topic Modelling to extract abstract topics and keywords
- Visualize topics and keywords
Increase the search ranking of a website by SEO optimization
- Leverage Social Media Channels of customer org for content optimization by extracting the trending keywords.
- Improve Search Ranking by using the trending Keywords in meta data as SEO keywords. Finding the Trending Keywords
- Understand the User Preferences using Topic Model
- Build Statistical Model to discover Abstract Topics from a collection of documents(tweets/posts) that has multiple topics which are divided in clusters of similar keywords, top key clusters are identified and most common keywords are extracted.
Why is the solution unique
- The approach adopts both Topic Modelling and clustering techniques. This helps not only in identifying relevant key words but also provides the theme of the content less than 5 minutes.
- Ability to process huge volumes of documents, social media posts etc.
- The algorithms used are open source, so no licensing and operational cost.
Features/BP diagram of the solution
