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US 11,379,548 B2Granted
Analyzing concepts over time
AssigneeInternational Business Machines Corporation
InventorsTin Kam Ho, Luis A. Lastras-Montano, Oded Shmueli
Life of this patent
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Abstract
A method and apparatus are provided for automatically generating and processing first and second concept vector sets extracted, respectively, from a first set of concept sequences and from a second, temporally separated, concept sequences by performing a natural language processing (NLP) analysis of the first concept vector set and second concept vector set to detect changes in the corpus over time by identifying changes for one or more concepts included in the first and/or second set of concept sequences.
Claims20
A method, in an information handling system comprising a processor and a memory, for analyzing concept vectors over time to detect changes in a corpus, the method comprising:
- generating, by the system, a first concept vector set V1, . . . , Vk derived from a first set of concept sequences over k concepts C1, . . . , Ck that are extracted from the corpus and applied to a vector learning component;
- generating, by the system, a second concept vector set V′1, . . . , V′k+b derived from a concatenation of the first set of concept sequences and a second set of concept sequences over k old and b new concepts Ck+1, . . . , Ck+b that are extracted from the corpus and applied to a vector learning component, where the second set of concept sequences is effectively collected after collection of the first set of concept sequences;
- identifying, by the system, a field vector VF for a specified field of interest represented by one or more concept vectors in the first concept vector set;
- identifying, by the system, a field vector V′F for the specified field of interest represented by one or more concept vectors in the second concept vector set;
- and
- performing, by the system, a natural language processing (NLP) analysis of the first concept vector set and second concept vector set to identify one or more emerging concepts Cj having corresponding emerging concept vectors V′j, l<j<k+b which meet at least the following conditions:
- (1) each emerging concept Cj occurs a specified minimum occurrence in the second set of concept sequences;
- (2) each corresponding emerging concept vector V′j meets a minimum similarity requirement to the field vector V′F;
- and
- (3) each emerging concept Cj is either one of the b new concepts, or is one of the k old concepts having an emerging concept vector V′j which has greater affinity to the field vector V′F than the affinity of the original vector Vj to the original field vector VF.
7 more elements
An information handling system comprising:
- one or more processors;
- a memory coupled to at least one of the processors;
- a set of instructions stored in the memory and executed by at least one of the processors to analyze concept vectors over time to detect changes in a corpus, wherein the set of instructions are executable to perform actions of:
- generating, by the system, a first concept vector set V1, . . . , Vk derived from a first set of concept sequences over k concepts C1, . . . , Ck that are extracted from the corpus and applied to a vector learning component;
- generating, by the system, a second concept vector set V′1, . . . , V′k+b derived from a concatenation of the first set of concept sequences and a second set of concept sequences over k old and b new concepts Ck+1, . . . , Ck+b that are extracted from the corpus and applied to a vector learning component, where the second set of concept sequences is effectively collected after collection of the first set of concept sequences;
- identifying, by the system, a field vector VF for a specified field of interest represented by one or more concept vectors in the first concept vector set;
- identifying, by the system, a field vector V′F for the specified field of interest represented by one or more concept vectors in the second concept vector set;
- and
- performing, by the system, a natural language processing (NLP) analysis of the first concept vector set and second concept vector set to identify one or more emerging concepts Cj having corresponding emerging concept vectors V′j, l<j<k+b which meet at least the following conditions:
- (1) each emerging concept Cj occurs a specified minimum occurrence in the second set of concept sequences;
- (2) each corresponding emerging concept vector V′j meets a minimum similarity requirement to the field vector V′F;
- and
- (3) each emerging concept Cj is either one of the b new concepts, or is one of the k old concepts having an emerging concept vector V′j which has greater affinity to the field vector V′F than the affinity of the original vector Vj to the original field vector VF.
10 more elements
A computer program product stored in a non-transitory computer readable storage medium, comprising computer instructions that, when executed by an information handling system, causes the system to analyze concept vectors over time to detect changes in a corpus by performing actions comprising:
- generating, by the system, a first concept vector set V1, . . . , Vk derived from a first set of concept sequences over k concepts C1, . . . , Ck that are extracted from the corpus and applied to a vector learning component;
- generating, by the system, a second concept vector set V′1, . . . , V′k+b derived from a concatenation of the first set of concept sequences and a second set of concept sequences over k old and b new concepts Ck+1, . . . , Ck+b that are extracted from the corpus and applied to a vector learning component, where the second set of concept sequences is effectively collected after collection of the first set of concept sequences;
- identifying, by the system, a field vector VF for a specified field of interest represented by one or more concept vectors in the first concept vector set;
- identifying, by the system, a field vector V′F for the specified field of interest represented by one or more concept vectors in the second concept vector set;
- and
- performing, by the system, a natural language processing (NLP) analysis of the first concept vector set and second concept vector set to identify one or more emerging concepts Cj having corresponding emerging concept vectors V′j, l<j<k+b which meet at least the following conditions:
- (1) each emerging concept Cj occurs a specified minimum occurrence in the second set of concept sequences;
- (2) each corresponding emerging concept vector V′j meets a minimum similarity requirement to the field vector V′F;
- and
- (3) each emerging concept Cj is either one of the b new concepts, or is one of the k old concepts having an emerging concept vector V′j which has greater affinity to the field vector V′F than the affinity of the original vector Vj to the original field vector VF.
7 more elements
Dependencies are inferred from the claim text.