Fingerprint-Based Near-Duplicate Document Detection with Applications to SNS Spam Detection
Social networking has been used widely by millions of people over the world. It has become the most popular way for people who want to connect and interact online with their friends. Currently, there are many social networking sites, for instance, Facebook, My Space, and Twitter, with a huge number...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-05-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2014/612970 |
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| _version_ | 1849704320785711104 |
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| author | Phuc-Tran Ho Sung-Ryul Kim |
| author_facet | Phuc-Tran Ho Sung-Ryul Kim |
| author_sort | Phuc-Tran Ho |
| collection | DOAJ |
| description | Social networking has been used widely by millions of people over the world. It has become the most popular way for people who want to connect and interact online with their friends. Currently, there are many social networking sites, for instance, Facebook, My Space, and Twitter, with a huge number of active users. Therefore, they are also good places for spammers or cheaters who want to steal the personal information of users or advertise their products. Recently, many proposed methods are applied to detect spam comments on social networks with different techniques. In this paper, we propose a similarity-based method that combines fingerprinting technique with trie-tree data structure and meet-in-the-middle approach in order to achieve a higher accuracy in spam comments detection. Using our proposed approach, we are able to detect around 98% spam comments in our dataset. |
| format | Article |
| id | doaj-art-04a8e8d83ed54c06a437f898facd2bff |
| institution | DOAJ |
| issn | 1550-1477 |
| language | English |
| publishDate | 2014-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-04a8e8d83ed54c06a437f898facd2bff2025-08-20T03:16:47ZengWileyInternational Journal of Distributed Sensor Networks1550-14772014-05-011010.1155/2014/612970612970Fingerprint-Based Near-Duplicate Document Detection with Applications to SNS Spam DetectionPhuc-Tran Ho0Sung-Ryul Kim1 Department of Advanced Technology Fusion, Konkuk University, Seoul 143-701, Republic of Korea Department of Internet & Multimedia Engineering, Konkuk University, Seoul 143-701, Republic of KoreaSocial networking has been used widely by millions of people over the world. It has become the most popular way for people who want to connect and interact online with their friends. Currently, there are many social networking sites, for instance, Facebook, My Space, and Twitter, with a huge number of active users. Therefore, they are also good places for spammers or cheaters who want to steal the personal information of users or advertise their products. Recently, many proposed methods are applied to detect spam comments on social networks with different techniques. In this paper, we propose a similarity-based method that combines fingerprinting technique with trie-tree data structure and meet-in-the-middle approach in order to achieve a higher accuracy in spam comments detection. Using our proposed approach, we are able to detect around 98% spam comments in our dataset.https://doi.org/10.1155/2014/612970 |
| spellingShingle | Phuc-Tran Ho Sung-Ryul Kim Fingerprint-Based Near-Duplicate Document Detection with Applications to SNS Spam Detection International Journal of Distributed Sensor Networks |
| title | Fingerprint-Based Near-Duplicate Document Detection with Applications to SNS Spam Detection |
| title_full | Fingerprint-Based Near-Duplicate Document Detection with Applications to SNS Spam Detection |
| title_fullStr | Fingerprint-Based Near-Duplicate Document Detection with Applications to SNS Spam Detection |
| title_full_unstemmed | Fingerprint-Based Near-Duplicate Document Detection with Applications to SNS Spam Detection |
| title_short | Fingerprint-Based Near-Duplicate Document Detection with Applications to SNS Spam Detection |
| title_sort | fingerprint based near duplicate document detection with applications to sns spam detection |
| url | https://doi.org/10.1155/2014/612970 |
| work_keys_str_mv | AT phuctranho fingerprintbasednearduplicatedocumentdetectionwithapplicationstosnsspamdetection AT sungryulkim fingerprintbasednearduplicatedocumentdetectionwithapplicationstosnsspamdetection |