US 2022/0012431 A1Published application

Determining semantic similarity of texts based on sub-sections thereof

AssigneeServiceNow, Inc.

InventorsOmer Anil Turkkan, Firat Karakusoglu, Sriram Palapudi

Life of this patent

Estimating the term…

Loading patent…

Abstract

Systems and methods are provided to compare a target sample of text to a set of textual records, each textual record including a sample of text and an indication of one or more segments of text within the sample of text. Semantic similarity values between the target sample of text and each of the textual records are determined. Determining a particular semantic similarity value between the target sample of text and a particular textual record of the corpus includes: (i) determining individual semantic similarity values between the target sample of text and each of the segments of text indicated by the particular textual record, and (ii) generating the particular semantic similarity value between the target sample of text and the particular textual record based on the individual semantic similarity values. A textual record is then selected based on the semantic similarities.

Claims20

Dependent claims

A system comprising:

a processor;
and
a memory, accessible by the processor, the memory storing instructions that, when executed by the processor, cause the processor to perform operations comprising:
accessing a corpus comprising a plurality of textual records;
generating, via a machine learning model, indications of one or more respective segments of text within each of the textual records in the corpus;
obtaining, from a client device, a target sample of text;
generating respective record semantic similarity values between the target sample of text and each of the textual records in the corpus, comprising, for each of the textual records in the corpus:
determining one or more respective segment semantic similarity values between the target sample of text and the one or more segments of text within the textual record;
and
generating the respective record semantic similarity value between the target sample of text and the textual record based on the one or more respective segment semantic similarity values;
selecting from the corpus, based on the generated record semantic similarity values, a particular textual record having the highest respective record semantic similarity value for the target sample of text;
and
providing, to the client device, a representation of the particular textual record.

10 more elements

A computer-implemented method comprising:

accessing, by a server device, a corpus comprising a plurality of textual records;
generating indications of one or more respective segments of text within each of the textual records in the corpus;
receiving, by the server device and from a client device, a target sample of text;
generating respective record, by the server device, semantic similarity values between the target sample of text and each of the textual records in the corpus, comprising, for each of the textual records in the corpus:
determining one or more respective segment semantic similarity values between the target sample of text and the one or more segments of text within the textual record;
and
generating the respective record semantic similarity value between the target sample of text and the textual record based on the one or more respective segment semantic similarity values;
selecting from the corpus, based on the generated record semantic similarity values, a particular textual record having the highest respective semantic similarity value for the target sample of text;
and
providing, by the server device and to the client device, a representation of the particular textual record.

7 more elements

An article of manufacture including a non-transitory computer-readable medium, having stored thereon program instructions that, upon execution by a computing system, cause the computing system to perform operations comprising:

accessing, by a server device, a corpus comprising a plurality of textual records;
generating indications of one or more respective segments of text within each of the textual records in the corpus;
receiving, by the server device and from a client device, a target sample of text;
generating respective record, by the server device, semantic similarity values between the target sample of text and each of the textual records in the corpus, comprising, for each of the textual records in the corpus:
determining one or more respective segment semantic similarity values between the target sample of text and the one or more segments of text within the textual record;
and
generating the respective record semantic similarity value between the target sample of text and the textual record based on the one or more respective segment semantic similarity values;
selecting from the corpus, based on the generated record semantic similarity values, a particular textual record having the highest respective semantic similarity value for the target sample of text;
and
providing, by the server device and to the client device, a representation of the particular textual record.

7 more elements

Dependencies are inferred from the claim text.

Facts

Application: 17/448,667Filed 23 Sep 2021
Priority: 22 Mar 2019
Published: 13 Jan 2022
Term ends: Not estimatedThe source records don’t support an estimate.

Classification5 codes

G06F 16/3347
Query execution: using vector based model
G06F 40/30
Handling natural language data: semantic analysis
G06F 40/205
Natural language analysis: parsing
G06F 40/284
Recognition of textual entities: lexical analysis, e.g. tokenisation or collocates

Family

Application16/362,187Continuation · filed 22 Mar 2019
Application17/448,667Continuation
US 11,151,325 B2Related patent
US 12,299,397 B2Related patent
US 2020/0302018 A1Published application
US 2022/0012431 A1This patent

From the US filing history. Foreign family members aren’t listed.