Patent ID: 11875113
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 9:
10. A computer system for semantic matching, comprising:
one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising:
pre-processing and normalizing a job title by segmenting the job title into single word tokens and removing informal words, geographic data and numeric data from the job title;
deconstructing the job title based on at least one semantic element, wherein the job title includes 3 semantic elements;
training a machine learning model using at least continuous bag of words;
creating a contextual word representation of the job title using the at least one semantic element of the job title, wherein the contextual word representation of the job title is refined based on an industry of a job;
adjusting the machine learning model based on the industry of the job and computing a similarity score for each of the at least one semantic element of the job title using a cosine distance of the contextual word representation;
adjusting the machine learning model to determine a similarity match based on a general purpose and a domain specific match as determined by a concurrence probability relevant to at least a lexical interpretation; and
applying a weight to the computed similarity score, wherein the weight is a differential weight based on a word entropy score or a term frequency-inverse document frequency (tf-idf) score, and making a final match assessment which details how a match category of high, medium, or low, corresponding to a generated match score, was determined.