18117281. CLIPBOARD BASED SEARCH TERM PREDICTION simplified abstract (INTERNATIONAL BUSINESS MACHINES CORPORATION)

CLIPBOARD BASED SEARCH TERM PREDICTION

Organization Name

INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor(s)

Aaron K. Baughman of Cary NC (US)

Shikhar Kwatra of San Jose CA (US)

Iranna Dharmaraya Ankad of Bengaluru (IN)

Utpal Mangla of Toronto (CA)

CLIPBOARD BASED SEARCH TERM PREDICTION - A simplified explanation of the abstract

This abstract first appeared for US patent application 18117281 titled 'CLIPBOARD BASED SEARCH TERM PREDICTION

Simplified Explanation: The patent application describes a method of predicting search queries based on a user's search history and the probability of selecting relevant and irrelevant samples from a set of contents. This prediction is presented to the user for selection when they indicate an intent to perform a search.

• Using a probability distribution and search result history
• Computing the probability of selecting relevant and irrelevant samples
• Weighting each content in the set of contents based on the probability distribution
• Generating a set of predicted searches using the weighted set of contents
• Presenting the set of predicted searches for selection
• Performing the selected search within the set of predicted searches

Potential Applications: This technology could be applied in search engines, recommendation systems, and personalized content delivery platforms to enhance user experience and improve search accuracy.

Problems Solved: - Predicting user search queries accurately - Providing relevant search suggestions based on user behavior - Improving search efficiency and effectiveness

Benefits: - Enhanced user experience - Increased search accuracy - Time-saving for users - Personalized search results

Commercial Applications: Predictive search technology can be utilized in online advertising, e-commerce platforms, and information retrieval systems to tailor content and advertisements to individual user preferences, leading to higher engagement and conversion rates.

Questions about Predictive Search Technology: 1. How does predictive search technology improve user search experience? 2. What are the potential privacy concerns associated with predictive search technology?

Frequently Updated Research: Researchers are constantly exploring ways to improve predictive search algorithms by incorporating machine learning and natural language processing techniques to enhance the accuracy and relevance of search predictions.

Original Abstract Submitted

Using a probability distribution and a search result history, a probability of selecting a specified number of relevant samples and a specified number of irrelevant samples from a set of contents is computed, each content in the set of contents comprising a content copied to a first system clipboard of a first device. Using the probability distribution, each content in the set of contents is weighted. Using the weighted set of contents, a set of predicted searches is generated. The set of predicted searches is presented for selection responsive to an indication of intent to perform a search. A selected search within the set of predicted searches is caused to be performed.