发明名称 CONTEXT-BASED DATA GRAVITY WELLS
摘要 A processor-implemented method, system, and/or computer program product defines multiple context-based data gravity wells on a context-based data gravity wells membrane. Non-contextual data objects are associated with context objects to define synthetic context-based objects. The synthetic context-based objects are parsed into an n-tuple that includes a pointer to one of the non-contextual data objects, a probability that a non-contextual data object has been associated with a correct context object, and a weighting factor of importance of the synthetic context-based object. A virtual mass of each parsed synthetic context-based object is calculated, in order to define a shape of multiple context-based data gravity wells that are created when synthetic context-based objects are pulled into each of the context-based data gravity well frameworks on a context-based data gravity wells membrane.
申请公布号 US2014188887(A1) 申请公布日期 2014.07.03
申请号 US201313732517 申请日期 2013.01.02
申请人 INTERNATIONAL BUSINESS MACHINES CORPORATION 发明人 ADAMS SAMUEL S.;FRIEDLANDER ROBERT R.;KRAEMER JAMES R.;LINTON JEB R.
分类号 G06F17/30 主分类号 G06F17/30
代理机构 代理人
主权项 1. A processor-implemented method of defining multiple context-based data gravity wells on a context-based data gravity wells membrane, the processor-implemented method comprising: receiving, by a processor, a data stream of non-contextual data objects, wherein each of the non-contextual data objects ambiguously relates to multiple subject-matters; associating, by the processor, one of the non-contextual data objects with a context object to define a synthetic context-based object, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of said one of the non-contextual data objects; parsing, by the processor, the synthetic context-based object into an n-tuple, wherein the n-tuple comprises a pointer to said one of the non-contextual data objects, a probability that a non-contextual data object has been associated with a correct context object, and a weighting factor of importance of the synthetic context-based object; calculating, by the processor, a virtual mass of a parsed synthetic context-based object, wherein the virtual mass of the parsed synthetic context-based object is derived from a formula of: P(C)×Wt(S),  where P(C) is the probability that the non-contextual data object has been associated with the correct context object, and where Wt(S) is the weighting factor of importance of the synthetic context-based object; creating, by the processor, multiple context-based data gravity well frameworks on a context-based data gravity wells membrane, wherein each of the multiple context-based data gravity well frameworks comprises at least one non-contextual data object and at least one context object, and wherein the context-based data gravity wells membrane is a virtual mathematical membrane that is capable of supporting multiple context-based data gravity wells; transmitting, by the processor, multiple parsed synthetic context-based objects to the context-based data gravity wells membrane; and defining, by the processor, multiple context-based data gravity wells according to the virtual mass of multiple parsed synthetic context-based objects that are pulled into each of the context-based data gravity well frameworks, wherein each of the multiple parsed synthetic context-based objects is pulled into a particular context-based data gravity well in response to values from its n-tuple matching said at least one non-contextual data object and said at least one context object in said particular context-based data gravity well.
地址 Armonk NY US