Our vision at Semantic Reviews is to build a decision making platform for buying online and physical world, using social and semantic collective intelligence of users whenever they want to buy a product, choose a brand, plan a trip or speculating a stock or consulting a doctor or diagnostics. 

Problem Statement:
The key factors, shoppers on multi-channel commerce (web.mobile, retail stores and kiosks) rely upon are product reviews, ratings and recommendations for making their buying decisions.The problems with the current model of reviews and ratings are that they are verbose and quantitative (users spend a minimum of 4hours to 1week in reading reviews before buying),tough to filter and search, collected within a week from buying the product/service resulting in uninformed personal opinion of reviewers and can also contain fake reviews. Friend Recommendations are often disconnected from shopping activity and automated recommendations often lack insights, user preferences and unpredic...
Our vision at Semantic Reviews is to build a decision making platform for buying online and physical world, using social and semantic collective intelligence of users whenever they want to buy a product, choose a brand, plan a trip or speculating a stock or consulting a doctor or diagnostics. 

Problem Statement:
The key factors, shoppers on multi-channel commerce (web.mobile, retail stores and kiosks) rely upon are product reviews, ratings and recommendations for making their buying decisions.The problems with the current model of reviews and ratings are that they are verbose and quantitative (users spend a minimum of 4hours to 1week in reading reviews before buying),tough to filter and search, collected within a week from buying the product/service resulting in uninformed personal opinion of reviewers and can also contain fake reviews. Friend Recommendations are often disconnected from shopping activity and automated recommendations often lack insights, user preferences and unpredictable product-interest combinations.

Solution:
Semantic Ratings and Reviews:
○ Leveraging patented technology in ensembled learning,semantic extraction,structured crawling,sentiment analysis &collective intelligence techniques to provide meaningful& Contextual Attribute level ratings which provides shoppers with a quick snapshot of what they are looking for in a product.
○ Differentiate aggregated public reviews from influential circle(friends&family) reviews & product expert reviews with overall product affinity & buying trends.
○ Auto-generation of text/video reviews

Recommendations
○ Preference for influential circle recommendations data over collaborative filtering based
○ Ever changing user preferences&social circles are taken into consideration for dynamic recommendations

We are in the process of filing US and India Patents or the following aspects of our product.
1. Structured Crawling using dom obfuscation and client side script
2. Targeted Marketing leveraging Product and Customer semantics
3.Review based Product Trend prediction
4. Social Vote based Product Ranking
5. Fake Review and Noise Elimination
6. Auto Construction of Text Reviews based on attribute level rating
7. Analytics and Social Recommendation and Reviews leveraging a combination of Ensembled Learning and Text Mining.

With our patented technology coupled with an adaptable business model, we are at a unique position to become a market leader in this segment.
More information

Advisors

Alex Croft
Admin
Alex Croft

Employees

Venkata Ramana Reddy D
Admin
Venkata Ramana Reddy D
Sreenivas Sigharam
Admin
Sreenivas Sigharam
Vivek Reddy
Admin
Vivek Reddy