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smsspamcollection (2 files)
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Type: Dataset
Tags:
Bibtex:
Tags:
Bibtex:
@article{, title= {SMS Spam Collection Data Set }, journal= {}, author= {Tiago A. Almeida and José María Gómez Hidalgo}, year= {}, url= {}, abstract= {==Data Set Information: This corpus has been collected from free or free for research sources at the Internet: -> A collection of 425 SMS spam messages was manually extracted from the Grumbletext Web site. This is a UK forum in which cell phone users make public claims about SMS spam messages, most of them without reporting the very spam message received. The identification of the text of spam messages in the claims is a very hard and time-consuming task, and it involved carefully scanning hundreds of web pages. The Grumbletext Web site is: [Web Link]. -> A subset of 3,375 SMS randomly chosen ham messages of the NUS SMS Corpus (NSC), which is a dataset of about 10,000 legitimate messages collected for research at the Department of Computer Science at the National University of Singapore. The messages largely originate from Singaporeans and mostly from students attending the University. These messages were collected from volunteers who were made aware that their contributions were going to be made publicly available. The NUS SMS Corpus is avalaible at: [Web Link]. -> A list of 450 SMS ham messages collected from Caroline Tag's PhD Thesis available at [Web Link]. -> Finally, we have incorporated the SMS Spam Corpus v.0.1 Big. It has 1,002 SMS ham messages and 322 spam messages and it is public available at: [Web Link]. This corpus has been used in the following academic researches: ==Source: Tiago A. Almeida (talmeida ufscar.br) Department of Computer Science Federal University of Sao Carlos (UFSCar) Sorocaba, Sao Paulo - Brazil José María Gómez Hidalgo (jmgomezh yahoo.es) R&D Department Optenet Las Rozas, Madrid - Spain ==Publication and More Information We offer a comprehensive study of this corpus in the following papers. These works present a number of interesting statistics, studies and baseline results for many traditional machine learning methods. Almeida, T.A., Gómez Hidalgo, J.M., Yamakami, A. Contributions to the Study of SMS Spam Filtering: New Collection and Results. Proceedings of the 2011 ACM Symposium on Document Engineering (DOCENG'11), Mountain View, CA, USA, 2011. Gómez Hidalgo, J.M., Almeida, T.A., Yamakami, A. On the Validity of a New SMS Spam Collection. Proceedings of the 11th IEEE International Conference on Machine Learning and Applications (ICMLA'12), Boca Raton, FL, USA, 2012. Almeida, T.A., Gómez Hidalgo, J.M., Silva, T.P. Towards SMS Spam Filtering: Results under a New Dataset. International Journal of Information Security Science (IJISS), 2(1), 1-18, 2013. ==Attribute Information: The collection is composed by just one text file, where each line has the correct class followed by the raw message. We offer some examples bellow: ham What you doing?how are you? ham Ok lar... Joking wif u oni... ham dun say so early hor... U c already then say... ham MY NO. IN LUTON 0125698789 RING ME IF UR AROUND! H* ham Siva is in hostel aha:-. ham Cos i was out shopping wif darren jus now n i called him 2 ask wat present he wan lor. Then he started guessing who i was wif n he finally guessed darren lor. spam FreeMsg: Txt: CALL to No: 86888 & claim your reward of 3 hours talk time to use from your phone now! ubscribe6GBP/ mnth inc 3hrs 16 stop?txtStop spam Sunshine Quiz! Win a super Sony DVD recorder if you canname the capital of Australia? Text MQUIZ to 82277. B spam URGENT! Your Mobile No 07808726822 was awarded a L2,000 Bonus Caller Prize on 02/09/03! This is our 2nd attempt to contact YOU! Call 0871-872-9758 BOX95QU Note: the messages are not chronologically sorted. ==Citation Request: If you find this dataset useful, you make a reference to our paper and the web page: [Web Link] in your papers, research, etc; Send us a message to talmeida ufscar.br or jmgomezh yahoo.es in case you make use of the corpus. We would like to thank Min-Yen Kan and his team for making the NUS SMS Corpus available.}, keywords= {}, terms= {} }