MY189086A - System and method for dynamic entity sentiment analysis - Google Patents

System and method for dynamic entity sentiment analysis

Info

Publication number
MY189086A
MY189086A MYPI2018001919A MYPI2018001919A MY189086A MY 189086 A MY189086 A MY 189086A MY PI2018001919 A MYPI2018001919 A MY PI2018001919A MY PI2018001919 A MYPI2018001919 A MY PI2018001919A MY 189086 A MY189086 A MY 189086A
Authority
MY
Malaysia
Prior art keywords
sentiment
sentences
entity
module
topic
Prior art date
Application number
MYPI2018001919A
Inventor
Duc Nghia Pham Dr
Farid Bin Noor Batcha Mohamed
Khairuddin Bin Ahamad Muhammad
A/P Ulanganathan Thenmalar
Original Assignee
Mimos Berhad
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Mimos Berhad filed Critical Mimos Berhad
Priority to MYPI2018001919A priority Critical patent/MY189086A/en
Priority to PCT/MY2019/050092 priority patent/WO2020101477A1/en
Publication of MY189086A publication Critical patent/MY189086A/en

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/279—Recognition of textual entities
    • G06F40/289—Phrasal analysis, e.g. finite state techniques or chunking
    • G06F40/295—Named entity recognition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/279—Recognition of textual entities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/30—Semantic analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/205—Parsing
    • G06F40/211—Syntactic parsing, e.g. based on context-free grammar [CFG] or unification grammars

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Computational Linguistics (AREA)
  • General Health & Medical Sciences (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

The present invention provides a dynamic entity sentiment analysis (DESA) system (1). The system (1) include an entity search portal (10) including a graphical user interface (GUI); an entity recognition module (20) electronically coupled with the entity search portal (10) to receives the input keyword and to search for matching alternative keywords; a sentence grouping module (30) electronically coupled with the entity recognition module (20) for crawling a set of matching articles; a topic extraction module (40) for receiving the blocks of sentences, and processing each and every block of sentences to extract the keywords so as to provide identified topics, identified subjects and topic popularity; a sentence weightage module (50) for receiving blocks of sentences and topic popularities, and extracting adjectives from the input sentences to provide a weighted sentiment score of each block of sentences; a sentiment scoring module (60) for receiving the blocks of sentences, weighted sentiment scores for the respective block of sentences, and performing sentiment analysis to provide a sentiment score value within a range of value; a sentiment score aggregator module (70) for receiving the sentiment scores of each block of sentences relating to the entity, and aggregating the scores from each sentiment per entity per document per topic to provide list of aggregated sentiment scores of entity, document and topic; a sentiment variance module (80) for receiving the topic, popularity, document metadata, sentiment per entity, sentiment per document, and sentiment per topic, and scales the sentiment values according to the inputs using an algorithm to provide final sentiment score on each entity based on sentences, topics and documents, and document type being extracted from the metadata; and a sentiment network graph display module (90) for displaying the sentiment score values on the GUI. A method thereof is also provided. FIG 1
MYPI2018001919A 2018-11-14 2018-11-14 System and method for dynamic entity sentiment analysis MY189086A (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
MYPI2018001919A MY189086A (en) 2018-11-14 2018-11-14 System and method for dynamic entity sentiment analysis
PCT/MY2019/050092 WO2020101477A1 (en) 2018-11-14 2019-11-14 System and method for dynamic entity sentiment analysis

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
MYPI2018001919A MY189086A (en) 2018-11-14 2018-11-14 System and method for dynamic entity sentiment analysis

Publications (1)

Publication Number Publication Date
MY189086A true MY189086A (en) 2022-01-25

Family

ID=70730720

Family Applications (1)

Application Number Title Priority Date Filing Date
MYPI2018001919A MY189086A (en) 2018-11-14 2018-11-14 System and method for dynamic entity sentiment analysis

Country Status (2)

Country Link
MY (1) MY189086A (en)
WO (1) WO2020101477A1 (en)

Families Citing this family (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111813919B (en) * 2020-06-24 2024-05-28 华中师范大学 MOOC course evaluation method based on syntactic analysis and keyword detection
CN111950273B (en) * 2020-07-31 2023-09-01 南京莱斯网信技术研究院有限公司 Automatic network public opinion emergency identification method based on emotion information extraction analysis
CN112560469B (en) * 2020-12-29 2023-07-04 珠海横琴博易数据技术有限公司 Method and system for automatically exploring Chinese text theme
US11853700B1 (en) * 2021-02-12 2023-12-26 Optum, Inc. Machine learning techniques for natural language processing using predictive entity scoring
CN113360646B (en) * 2021-06-02 2023-09-19 华院计算技术(上海)股份有限公司 Text generation method, device and storage medium based on dynamic weight
CN114706972B (en) * 2022-03-21 2024-06-18 北京理工大学 Automatic generation method of unsupervised scientific and technological information abstract based on multi-sentence compression
CN115952787B (en) * 2023-03-13 2023-05-12 北京澜舟科技有限公司 Emotion analysis method, system and storage medium for appointed target entity
CN117973946B (en) * 2024-03-29 2024-06-21 与同科技(北京)有限公司 Teaching-oriented data processing method and system

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2013525868A (en) * 2009-12-24 2013-06-20 ズオン−バン ミン System and method for determining sentiment expressed in a document
KR101423549B1 (en) * 2012-10-26 2014-08-01 고려대학교 산학협력단 Sentiment-based query processing system and method
US20150286627A1 (en) * 2014-04-03 2015-10-08 Adobe Systems Incorporated Contextual sentiment text analysis
US10242074B2 (en) * 2016-02-03 2019-03-26 Facebook, Inc. Search-results interfaces for content-item-specific modules on online social networks
US20180082389A1 (en) * 2016-09-20 2018-03-22 International Business Machines Corporation Prediction program utilizing sentiment analysis

Also Published As

Publication number Publication date
WO2020101477A1 (en) 2020-05-22

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