1. 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, at least a first concept vector set V1,. .. , Vk derived from a first set of concept sequences over k concepts that are extracted from the corpus and applied to a vector learning component; generating, by the system, at least a second concept vector set V′1,. .. , V′k+b derived from a second set of concept sequences over k old and b new concepts that are extracted from the corpus and applied to the vector learning component, where the second set of concept sequences is effectively collected after collection of the first set of concept sequences; and performing, by the system, 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 analyzing relationship strengths between concepts that persist in the first set of concept sequences and the second set of concept sequences to identify market trends for answering questions submitted to the information handling system by identifying vector changes for one or more concepts included in the first and/or second set of concept sequences, wherein analyzing relationship strengths comprises: computing, by the system, a first cosine distance between each vector pair Vi, Vj from the first concept vector set V1,. .. , Vk for all i≠j, 1≤i, j≤k; computing, by the system, a second cosine distance between each vector pair V′i, V′j from the second concept vector set V′1,. .. , V′k+b for all i≠j, 1≤i, j≤k; and identifying concept pairs from the first set of concept sequences whose interrelationship has changed by reporting each concept pair Vi, Vj whereby a subtraction of the second cosine distance from the first cosine distance exceeds a first specified reporting threshold.