Text Reuse Detection by Keyword Extraction for Telegram Channels

被引：0

作者：

Saki, Misam ^{[1
]}

Faili, Heshaam ^{[1
]}

Asadpour, Masoud ^{[1
]}

机构：

[1] Univ Tehran, Sch Elect & Comp Engn, Tehran, Iran

来源：

2017 25TH IRANIAN CONFERENCE ON ELECTRICAL ENGINEERING (ICEE) | 2017年

关键词：

Text Reuse; Text Similarity; Text Clustering; Keyword Extraction; Telegram;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Text reuse detection is the task of finding similar texts, which has many applications e.g. in plagiarism detection and analysis of information diffusion. The general approach to this problem is by detection of texts similarities in combination with other features such as time-stamp which can be used to specify the precedence of publishers e.g. to find the first publisher. In this article a method for finding similar texts has been proposed using keyword extraction which operates in linear time like LSH1 method. In addition, it supports dynamic inputs and does not depend on text vector dimensions. Our evaluations show, it has better performance in clustering quality measures and also run time.

引用

页码：1481 / 1484

页数：4

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