A new approach to filtering spam SMS: Motif Patterns
Along with the widespread of every technology, it comes with many problems. Mobile Short Message Service (SMS), which is widely used in mobile technologies, has brought many problems. The most important problem of SMS is unwanted messages named spam that are spread on the mobile network. Spam messa...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Gazi University
2018-06-01
|
| Series: | Gazi Üniversitesi Fen Bilimleri Dergisi |
| Subjects: | |
| Online Access: | http://dergipark.gov.tr/download/article-file/476007 |
| _version_ | 1797919640794431488 |
|---|---|
| author | Yılmaz Kaya Cüneyt Özdemir |
| author_facet | Yılmaz Kaya Cüneyt Özdemir |
| author_sort | Yılmaz Kaya |
| collection | DOAJ |
| description | Along with the widespread of every technology, it comes with many problems. Mobile Short Message Service (SMS), which is widely used in mobile technologies, has brought many
problems. The most important problem of SMS is unwanted messages named spam that are spread on the mobile network. Spam messages prevent mobile traffic and keep people busy
unnecessarily. In this study to filter SMS spam, a novel feature extraction method, motif pattern method, is proposed, which uses forms that composed of comparision on UTF-8 codes of characters. In the proposed motif pattern method, the appearance of the values entered into a window size (PB) defined on the unicodes of SMS is considered as a motif pattern. The frequencies of these motifs in the SMS are used as the feature vector. The motif types depend on the specified PB. Three benchmark datasets were used to test the motif pattern method. The success rate was 93.76%, 90.07% and 94.29%, respectively, for three sets of data. According to the observed results, it is seen that the proposed method is a successful feature extraction method from SMS messages in spam filtering. It is also thought that the motif method can be used in other text mining, natural language processing fields |
| first_indexed | 2024-04-10T13:48:45Z |
| format | Article |
| id | doaj.art-4e4c2c09025c451aba095ad7c8cfe3c6 |
| institution | Directory Open Access Journal |
| issn | 2147-9526 2147-9526 |
| language | English |
| last_indexed | 2024-04-10T13:48:45Z |
| publishDate | 2018-06-01 |
| publisher | Gazi University |
| record_format | Article |
| series | Gazi Üniversitesi Fen Bilimleri Dergisi |
| spelling | doaj.art-4e4c2c09025c451aba095ad7c8cfe3c62023-02-15T16:10:50ZengGazi UniversityGazi Üniversitesi Fen Bilimleri Dergisi2147-95262147-95262018-06-016243645010.29109/http-gujsc-gazi-edu-tr.372880A new approach to filtering spam SMS: Motif PatternsYılmaz KayaCüneyt ÖzdemirAlong with the widespread of every technology, it comes with many problems. Mobile Short Message Service (SMS), which is widely used in mobile technologies, has brought many problems. The most important problem of SMS is unwanted messages named spam that are spread on the mobile network. Spam messages prevent mobile traffic and keep people busy unnecessarily. In this study to filter SMS spam, a novel feature extraction method, motif pattern method, is proposed, which uses forms that composed of comparision on UTF-8 codes of characters. In the proposed motif pattern method, the appearance of the values entered into a window size (PB) defined on the unicodes of SMS is considered as a motif pattern. The frequencies of these motifs in the SMS are used as the feature vector. The motif types depend on the specified PB. Three benchmark datasets were used to test the motif pattern method. The success rate was 93.76%, 90.07% and 94.29%, respectively, for three sets of data. According to the observed results, it is seen that the proposed method is a successful feature extraction method from SMS messages in spam filtering. It is also thought that the motif method can be used in other text mining, natural language processing fieldshttp://dergipark.gov.tr/download/article-file/476007SMSMotif PatternSpam FilteringText Mining |
| spellingShingle | Yılmaz Kaya Cüneyt Özdemir A new approach to filtering spam SMS: Motif Patterns Gazi Üniversitesi Fen Bilimleri Dergisi SMS Motif Pattern Spam Filtering Text Mining |
| title | A new approach to filtering spam SMS: Motif Patterns |
| title_full | A new approach to filtering spam SMS: Motif Patterns |
| title_fullStr | A new approach to filtering spam SMS: Motif Patterns |
| title_full_unstemmed | A new approach to filtering spam SMS: Motif Patterns |
| title_short | A new approach to filtering spam SMS: Motif Patterns |
| title_sort | new approach to filtering spam sms motif patterns |
| topic | SMS Motif Pattern Spam Filtering Text Mining |
| url | http://dergipark.gov.tr/download/article-file/476007 |
| work_keys_str_mv | AT yılmazkaya anewapproachtofilteringspamsmsmotifpatterns AT cuneytozdemir anewapproachtofilteringspamsmsmotifpatterns AT yılmazkaya newapproachtofilteringspamsmsmotifpatterns AT cuneytozdemir newapproachtofilteringspamsmsmotifpatterns |