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Trang 6ASBTRACT
With the development of social networks, more and more information, topics are shared, discussed, and attracted a lot of users The problems of detecting, analyzing and predicting for hot topics are interested in research due to their high practical meaning in different application areas such as marketing and content promotion
Through studying the problem and related works, we have grasped and surveyed the hot topic prediction problem about the situation and challenges as well as the characteristics and predictive models used for the problem On that basis, we have proposed combining feature groups and developing methods to form positive and negative data samples for the problem of hot topic prediction Then we solve the problem as a binary classification problem with a machine learning approach, using supervised learning algorithms With the above suggestions for the dissertation, we have stated a problem, developed a solution, and conducted rigorous and complete evaluation experiments to create a comparative basis for the following works Experimental results were positive, improved with suggestions of the thesis, for the hot topic prediction problem
Trang 7/Ӡ,&$0Ĉ2$1
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DANH MӨC HÌNH 3
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Trang 10DANH MӨC HÌNH
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Trang 11DANH MӨC BҦNG BIӆU
BҧQJ&iFÿһFWUѭQJVӱ dөng 19BҧQJ&iFSKѭѫQJSKiSSKkQOӟp sӱ dөng 24Bҧng 3 KӃt quҧ thí nghiӋm vӅ tӯQJÿһFWUѭQJWUrQEӝ dӳ liӋu vӟLSKѭѫQJSKiSFKXҭn
bӏ dӳ liӋu theo cӵFÿҥi toàn cөc 25Bҧng 4 KӃt quҧ thí nghiӋm vӅ tӯQJÿһFWUѭQJWUrQEӝ dӳ liӋu vӟLSKѭѫQJSKiSFKXҭn
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Trang 12DANH MӨC TӮ VIӂT TҲT
API Application Programming Interface
GBDT Gradient Boosting Decision Tree
PAA Piecewise aggregate approximation
Trang 13&KѭѫQJ GIӞI THIӊU
1.1 TӘNG QUAN
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1 https://zephoria.com/top-15-valuable-facebook-statistics/
2 http://www.internetlivestats.com/twitter-statistics/
Trang 14PҥQJ [m KӝL FNJQJ ÿѭӧF WұQ GөQJ WURQJ YLӋF [k\ GӵQJ WKѭѫQJ KLӋX và TXҧQJ Ei QӝLdung
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WKӕQJ 7ZHYHQW [4] và Twitinfo [5] KѭӟQJ WLӃS FұQ GӵD WUrQ P{ KuQK KyD FKӫ ÿӅ
(Topic-modelling-based) [6]
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Trang 151.2 MӨC TIÊU CӪ$Ĉӄ TÀI
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1.5 CҨU TRÚC LUҰ19Ă1
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Bài toán dӵ EiR FKӫ ÿӅ QyQJ YӟL QKLӅX WrQ JӑL NKiF QKDX QKѭ ³topic attention forecast´ ³trend detection´ ³popularity prediction´ 0өF WLrX FKtQK FӫD EjL WRiQ Gӵ
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WUѭQJ Oj Burst Time Prediction in Cascades [16], Emerging Product Topics Prediction in Social Media without Social Structure Information [17] Các công
WUuQKQj\ÿmVӱGөQJvà trình bày khá rõ FiFÿһFWUѭQJYӅFKXӛLWKӡLJLDQWәQJTXiWQKyP ÿһF WUѭQJ YӅ GDR ÿӝQJ YӅ QJѭӡL GQJ FNJQJ QKѭ FiF TXDQ KӋ JLӳD FiF QJѭӡL
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3 'Rÿy trong OXұQYăQQj\ FK~QJW{LTX\ӃWÿӏQK[k\GӵQJEӝGӳOLӋXWӯEӝGӳOLӋXÿѭӧFVӱGөQJUӝQJUmLWURQJEjLWRiQSKiWKLӋQFKӫÿӅQyQJ(YHQW2012 QKѭÿmÿӅFұSӣWUrQ
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in Sina Weibo for News Earlier Report [7] ÿѭD UD FiF NӃW TXҧ Gӵ EiR YjR NKRҧQJ
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3 https://aminer.org/influencelocality
Trang 20&KѭѫQJ PHÂN TÍCH VҨ1Ĉӄ
3.1 PHÁT BIӆU BÀI TOÁN DӴ BÁO CHӪ Ĉӄ NÓNG
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.ӃW TXҧ SKөWKXӝFUҩWOӟQYjo ÿӝUӝQJFӫD NKXQJWKӡLJLDQ GӵEiR KLNKXQJWKӡLJLDQFyÿӝUӝQJOӟQNӃWTXҧGӵEiRPDQJWtQKFKXQJFKXQJ, NK{QJFKLWLӃWĈӝUӝQJFӫDNKXQJWKӡLJLDQFNJQJÿѭӧFÿLӅXFKӍQKWKHRWӯQJORҥLFKӫÿӅ VӟLFiFFKӫÿӅYӅFiFVҧQSKҭPNLQKGRDQKÿӝUӝQJFӫDNKXQJWKӡLJLDQFyWKӇÿѭӧFÿһWOjPӝWQJj\ VӟLFiFFKӫÿӅYӅVӵNLӋQYj WLQWӭFÿӝUӝQJÿѭӧFÿһWQKӓKѫQÿӇÿҧPEҧRWtQKFұSQKұW FӫDFiFNӃWTXҧGӵEiR
3.2 CÁC CÂU HӒI NGHIÊN CӬU
7ӯPөFWLrXFKtQKFӫDOXұQYăQOjÿӅ[XҩWJLҧLSKiSFKREjLWRiQGӵEiR FKӫÿӅQyQJ FK~QJW{LÿһWUDFiFFkXKӓL QJKLrQFӭXFөWKӇ QKѭVDX
1 ĈӇ ÿӅ [XҩW SKѭѫQJ SKiS Gӵ EiR WӕW FK~QJ W{L ÿm NKҧR ViW FiF ÿһF WUѭQJ ÿmÿѭӧFVӱGөQJFKREjLWRiQWURQJFiFF{QJWUuQKOLrQTXDQ 7ӯNӃWTXҧNKҧRViWckXKӓL1 OLrQTXDQÿӃQFiFÿһFWUѭQJÿѭӧFVӱGөQJFKREjLWRiQOjĈһFWUѭQJ
Trang 22QjRÿHPOҥLNӃWTXҧGӵEiRWӕWYjәQÿӏQK"/LӋXFyFiFKNӃWKӧS QjRÿӇnhóm
FiFÿһFWUѭQJYӟLQKDXÿӇFKRNӃWTXҧWӕWKѫQNK{QJ"
2 9ӟLFiFÿһFWUѭQJQKyPÿһFWUѭQJQKѭYұ\P{KuQKGӵEiRQjROjWKtFKKӧS"
3 1Kѭ SKҫQ SKiW ELӇX EjL WRiQ FK~QJ W{L QKұQ WKҩ\ QKX FҫX Gӵ EiR FӫD QJѭӡL
GQJÿѭӧFWKӇKLӋQTXDJLiWUӏFӫD FiFWKDPVӕܭ và u1KѭYұ\YӟLFiFÿһF
EjL ÿăQJ BjL WRiQ Fy QKLӅX GҥQJ Gӵ EiR khác nhau QKѭ ÿm ÿѭӧF WUuQK Ej\ ӣ SKҫQ
WUѭӟF VӟL GҥQJ Gӵ EiR WURQJ FiF NKXQJ WKӡL JLDQ NӃ WLӃS NӃW KӧS YӟL Gӵ EiR ÿӏQK
OѭӧQJ FKRPӭFÿӝQyQJFӫDFKӫÿӅ, công trình [12] JҫQÿk\ FKӍPӟLÿҥWNӃWTXҧFKѭD