发明申请
- 专利标题: SYSTEM AND METHODS FOR MATCHING POTENTIAL BUYERS AND SELLERS OF COMPLEX OFFERS
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申请号: US13181471申请日: 2011-07-12
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公开(公告)号: US20120310763A1公开(公告)日: 2012-12-06
- 发明人: Michael Meehan
- 申请人: Michael Meehan
- 主分类号: G06Q30/00
- IPC分类号: G06Q30/00
摘要:
A system for matching potential buyers and sellers of complex offers, comprising a plurality of data collection devices, each connected to at least one packet-based data network and adapted to collect data pertaining to a plurality of potential buyers or sellers of complex offers, a summary data generator software module operating on a server computer and connected via a data network to a database, an attribute index generator software module operating on a server computer and connected via a data network to the database, a categorization software module operating on a server computer and connected via a data network to the database, a buyer analysis engine software module operating on a server computer and connected via a data network to the database, an analysis engine software module operating on a server computer and connected via a data network to the database, and a matching engine software module operating on a server computer and connected via a data network to the database. Data collected by the data collection devices is stored in the database and is used by the summary data generator software module to generate a plurality of summary data elements pertaining to a potential buyer of a complex offer, and the plurality of summary data elements is stored in the database and used by the attribute index generator software module to generate attribute indices each based on at least two summary data elements using a weighted relational algorithm, and at least some data collected by the data collection devices is used by the buyer analysis engine software module to determine at least a probability that a buyer will buy a specific complex offer, and the marching engine software module uses an optimization algorithm to determine an optimal matching of potential buyers and complex offers based at least in part on a plurality of attribute indices and a likelihood to buy for each potential pair of offers and potential buyers.
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