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A real time clearing house for dynamic personal data Disclosure Number: IPCOM000240054D
Publication Date: 2014-Dec-29
Document File: 2 page(s) / 61K

Publishing Venue

The Prior Art Database


Disclosed is a system and method for semi automatic, real-time, context sensitive/dependent (dynamic) negotiation and clearing and matching of multiple buyers and sellers for time varying personal data, including job agent, user agent and clearing house as components. A Job Agent that convert coarse buyer requirements along with historical and context dependent information into sharp prices and specific information requests based on the current and historical prices and outcomes. A User Agent to convert coarse user preferences along with user context and forecasts of user context, into sharp thresholds and other information for use in the market along with ‘know when you don’t know’, i.e., when to query the user further as required. A trusted central Clearing House to match multiple buyers with sellers in an economically beneficial manner, while being sensitive to constraints and requirements on both sides. Clearing House includes to put up and eventually share the costs of initial investments to find the demography of user’s as per job requestor conditions wrt ‘required demography’ and other payments to ensure continued participation and ‘liquidity’.

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A real time clearing house for dynamic personal data

There are many personal (non-dynamic) data storehouses with large data sets. The proposed system look at dynamic markets for small (micro-transactional) data. There are many applications of such personal data such as advertising, smarter planet solution, and sense and optimize homes, electricity, water, cities, traffic, etc. Our proposed system does not focus on the applications (or what companies do with the data) but on how they can collect the data they need.

People are 'interested' in sharing data. However with growing fear of privacy issues, people are more reluctant to share data. Our system tries to incentivize the user to share data of the kind and at the time it is required.

The need of the house is just-in-time analytics using multi-sourced data to automate targeting and

personalization of data requests while guaranteeing fair means for data monetization respecting user requirements and constraint. In particular, an intelligent clearing house, e.g., that shouldn't request everything from everyone all the time. Moreover, the proposed system accounts for various contextual costs and constraints, and understand user constraints, respect their constraints and price accordingly, and understands requirements and constraints (deadlines) of sellers purchasers.

The input to our proposed system is buyer requirements (e.g., phone usage data, GPS data, browsing data, etc.) and seller constraints (e.g., phone hardware data, battery data, memory data, data-plan, etc.). Based on the input, our proposed system infers location, mode of transportation, their home/office address, their

purchasing pattern (e.g., whether user spends money online), their interests based on browsing data, and optimization b...