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Intellectual Frontiers

Welcome to Intellectual Frontiers

Shahid Shah's Intellectual Property Holdings

Patent Portfolio Highlights

Efficient Response Management System and Method for Crowdsourced Networks

In the rapidly evolving digital era, people increasingly turn to online crowdsourced networks to find answers and solutions to a wide array of queries and challenges. These platforms serve as invaluable resources, connecting individuals with a diverse and knowledgeable community eager to share insights and expertise. However, amid this digital revolution, a formidable problem has emerged, one that casts a shadow of doubt over the reliability and accuracy of the responses offered by the crowd of respondents. —>

Aggregating Trustworthy Rating Indicators for Enhancing Reputation Management

The existing landscape of online rating and review platforms is fraught with significant challenges in ensuring the accuracy, reliability, and authenticity of the information presented. These platforms host a plethora of reviews and ratings that can vary dramatically in their assessments of a given entity, such as a physician, primarily due to the diverse backgrounds and intentions of reviewers. Moreover, the trustworthiness of these reviews and the credibility of the reviewers themselves remain uncertain. —>

Integrated Healthcare System with Predictive Analytics and Risk Management through Social Networking

The existing landscape of device interaction and automation, spanning across various domains such as healthcare, manufacturing, and aviation, faces significant challenges. While there have been efforts to facilitate device interconnection and interaction, there remains a pressing need for more sophisticated systems and methods. These systems must not only streamline the communication between devices but also enable seamless integration into a socially aware network. The current state of device management falls short in providing comprehensive solutions to address these challenges. —>

Optimizing Rating Aggregation - A Method for Creating Accurate Aggregate Rating Indicators

Existing methods and systems for rating aggregation face significant challenges in providing accurate and reliable aggregate scores for entities, such as professionals or businesses. Review platforms often yield disparate ratings, influenced by various factors like reviewer subjectivity and the authenticity of reviews. While rating aggregation algorithms attempt to collate these ratings to form a single indicator of an entity’s credibility, they often fall short in delivering optimal and dependable results. —>