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Unsolicited emails, known as spam, are one of the fast growing and costly problems associated with the Internet today. Among the many proposed solutions, a technique using Bayesian filtering is considered as the most effective weapon against spam. Bayesian filtering works by evaluating the probability of different words appearing in legitimate and spam mails and then classifying them based on that probabilities.Most of the current spam email detection systems use keywords to detect spam emails.These keywords can be written as misspellings eg: baank or bannk instead of bank. Misspellings are changed from time to time and hence spam email detection system needs to constantly update the blacklist to detect spam emails containing misspellings. It"s impossible to predict all possible misspellings for a given keyword and add those to the blacklist. In this paper a better and more successful approach for improving E-mail content classification for spam control is proposed. It used the Word Stemming or Word Hashing Technique for improving the efficiency of the content based spam filter.The proposed system extract the base or stem of a misspelled or modified word, to detect spam emails. It considers every misspelled keyword applies a word stemming technique and passes the base word to the content based filter. Using a proposed if-then rule, we can decide whether or not this unknown mail is spam [1].This paper also provides an Email archiving solution which classifies the E-mail relating to a person,

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By automatically translating Indian sign language into English speech, a portable multimedia Indian sign language translation program can help the deaf and/or speaker connect with hearing people. It could act as a translator for those that do not understand sign language, eliminating the need for a mediator and allowing communication to take place in the speaker's native language. As a result, Deaf-Dumb people are denied regular educational opportunities. Uneducated Deaf-Dumb people have a difficult time communicating with members of their culture. We provide an incorporated Android application to help ignorant Deaf-Dumb people fit into society and connect with others. The newly launched program includes a straight forward keyboard translator that really can convert any term from Indian sign language to English. The proposed system is an interactive application program for mobile phones created with application software. The mobile phone is used to photograph Indian sign language gestures, while the operating system performs vision processing tasks and the constructed audio device output signals speech, limiting the need for extra devices and costs. The perceived latency between both the hand signals as well as the translation is reduced by parallel processing. This allows for a very quick translation of finger and hand motions. This is capable of recognizing one-handed sign representations of the numbers 0 through 9. The findings show that the results are highly reproducible, consistent, and accurate.