- Patent Title: System and method for evaluating semantic closeness of data files
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Application No.: US17520576Application Date: 2021-11-05
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Publication No.: US11977845B2Publication Date: 2024-05-07
- Inventor: Joseph Michael William Lyske , Nadine Kroher , Angelos Pikrakis
- Applicant: EMOTIONAL PERCEPTION AI LIMITED
- Applicant Address: GB London
- Assignee: EMOTIONAL PERCEPTION AI LIMITED
- Current Assignee: EMOTIONAL PERCEPTION AI LIMITED
- Current Assignee Address: GB London
- Agency: WORKMAN NYDEGGER
- Priority: GB 15695 2020.10.02
- Main IPC: G06F11/36
- IPC: G06F11/36 ; G06F8/75 ; G06F16/33 ; G06F16/438 ; G06F16/638 ; G06F16/68 ; G06F40/30 ; G06F40/45 ; G06N3/02 ; G06N3/049 ; G06N3/08 ; G06N7/01 ; H04L9/40 ; G06Q99/00 ; G06V20/40

Abstract:
The invention provides for the evaluation of semantic closeness of a source data file relative to candidate data files. The system includes an artificial neural network and processing intelligence that derives a property vector from extractable measurable properties of a data file. The property vector is mapped to related semantic properties for that same data file and such that, during ANN training, pairwise similarity/dissimilarity in property is mapped, during towards corresponding pairwise semantic similarity/dissimilarity in semantic space to preserve semantic relationships. Based on comparisons between generated property vectors in continuous multi-dimensional property space, the system and method assess, rank, and then recommend and/or filter semantically close or semantically disparate candidate files from a query from a user that includes the data file. Applications of the categorization and recommendation system apply to search tools, including identification of illicit materials or logically progressive associations between disparate files.
Public/Granted literature
- US20220107800A1 System and Method for Evaluating Semantic Closeness of Data Files Public/Granted day:2022-04-07
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