# US 2020/0401764 A1 · Systems and methods for generating abstractive text summarization > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2020/0401764 A1 - Document ID: US20200401764A1 - Status: Published application - Kind: A1 - Application number: 17/014,240 - Filed: 2020-09-08 - Published: 2020-12-24 - Earliest claimed: 2019-05-15 - Assignees: Beijing Didi Infinity Technology and Development Co., Ltd. - Applicants: Beijing Didi Infinity Technology and Development Co., Ltd. - Inventors: Kun Han; Haiyang Xu - Web page: https://patentgrep.com/patent/US20200401764A1 ## CPC - G06F 40/211: Syntactic parsing, e.g. based on context-free grammar [CFG] or unification grammars - G06F 40/56: Natural language generation - G06F 16/345: {Summarisation for human users} - G06F 16/93: Document management systems - G06F 40/205: Parsing - G06F 40/284: Lexical analysis, e.g. tokenisation or collocates - G06N 3/04: Architecture, e.g. interconnection topology - G06N 3/0442: characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU] - G06N 3/045: Combinations of networks - G06N 3/0455: Auto-encoder networks; Encoder-decoder networks - G06N 3/08: Learning methods - G06N 3/09: Supervised learning - G06N 7/01: Probabilistic graphical models, e.g. probabilistic networks - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract Embodiments of the disclosure provide systems and methods for generating text summarization. An exemplary system may include a processor and a non-transitory memory storing instructions that, when executed by the processor, cause the system to perform the various operations. The operations may include generating a document representation of a document. The document representation may include syntactic information. The operations may also include extracting salient information based on the document representation. The operations may further include generating a summary of the document based on the syntactic information and the salient information. ## Claims ### Claim 1 A system for generating text summarization, comprising: at least one processor; and at least one non-transitory memory storing instructions that, when executed by the at least one processor, cause the system to perform operations comprising: generating a document representation of a document, the document representation comprising syntactic information; extracting salient information based on the document representation; and generating a summary of the document based on the syntactic information and the salient information. ### Claim 2 (depends on 1) The system of claim 1, wherein the operations comprise: generating, by a syntactic parser, parsing trees for multiple text units in the document, the parsing trees comprising structural labels of the text units. ### Claim 3 (depends on 2) The system of claim 2, wherein the operations comprise: serializing each parsing tree into a sequence of tokens; and concatenating the sequences of tokens. ### Claim 4 (depends on 3) The system of claim 3, wherein the operations comprise: applying an encoder to the concatenated sequences of tokens to generate the document representation. ### Claim 5 (depends on 4) The system of claim 4, wherein the encoder comprises a bidirectional long short-term memory (BiLSTM). ### Claim 6 (depends on 1) The system of claim 1, wherein the operations comprise: applying a dynamic selective gate to the document representation to extract the salient information. ### Claim 7 (depends on 6) The system of claim 6, wherein the operations comprise: determining the dynamic selective gate based on text already generated in the summary. ### Claim 8 (depends on 1) The system of claim 1, wherein the operations comprise: determining, by a pointer-generator network, a switch probability based on context information; and determining, based on the switch probability, a word of the summary by selecting the word from the document or generating the word based on a vocabulary database. ### Claim 9 (depends on 8) The system of claim 8, wherein the operations comprise: determining, by the pointer-generator network, the context information based on the syntactic information. ### Claim 10 (depends on 1) The system of claim 1, wherein the operations comprise: minimizing a loss function comprising a coverage loss penalizing repeated selection of identical encoder information. ### Claim 11 A method for generating text summarization, comprising: generating a document representation of a document, the document representation comprising syntactic information; extracting salient information based on the document representation; and generating a summary of the document based on the syntactic information and the salient information. ### Claim 12 (depends on 11) The method of claim 11, comprising: generating, by a syntactic parser, parsing trees for multiple text units in the document, the parsing trees comprising structural labels of the text units. ### Claim 13 (depends on 12) The method of claim 12, comprising: serializing each parsing tree into a sequence of tokens; and concatenating the sequences of tokens ### Claim 14 (depends on 13) The method of claim 13, comprising: applying an encoder to the concatenated sequences of tokens to generate the document representation. ### Claim 15 (depends on 11) The method of claim 11, comprising: applying a dynamic selective gate to the document representation to extract the salient information. ### Claim 16 (depends on 15) The method of claim 15, comprising: determining the dynamic selective gate based on text already generated in the summary. ### Claim 17 (depends on 11) The method of claim 11, comprising: determining, by a pointer-generator network, a switch probability based on context information; and determining, based on the switch probability, a word of the summary by selecting the word from the document or generating the word based on a vocabulary database. ### Claim 18 (depends on 17) The method of claim 17, comprising: determining, by the pointer-generator network, the context information based on the syntactic information. ### Claim 19 (depends on 11) The method of claim 11, comprising: minimizing a loss function comprising a coverage loss penalizing repeated selection of identical encoder information. ### Claim 20 A non-transitory computer-readable medium having instructions stored thereon that, when executed by one or more processors, causes the one or more processors to perform a method for generating text summarization, the method comprising: generating a document representation of a document, the document representation comprising syntactic information; extracting salient information based on the document representation; and generating a summary of the document based on the syntactic information and the salient information.