2014 IEEE JAVA DATA MINING PROJECT A probabilistic approach to string transformation
- 1. GLOBALSOFT TECHNOLOGIES A Probabilistic Approach to String Transformation Abstract: Many problems in natural language processing, data mining, information retrieval, and bioinformatics can be formalized as string transformation, which is a task as follows. Given an input string, the system generates the k most likely output strings corresponding to the input string. This paper proposes a novel and probabilistic approach to string transformation, which is both accurate and efficient. The approach includes the use of a log linear model, a method for training the model, and an algorithm for generating the top k candidates, whether there is or is not a predefined dictionary. The log linear model is defined as a conditional probability distribution of an output string and a rule set for the transformation conditioned on an input string. The learning method employs maximum likelihood estimation for parameter estimation. The string generation algorithm based on pruning is guaranteed to generate the optimal top k candidates. The proposed method is applied to correction of spelling errors in queries as well as reformulation of queries in web search. Experimental results on large scale data show that the proposed approach is very accurate And efficient improving upon existing methods in terms of accuracy and efficiency in different settings. Architecture: IEEE PROJECTS & SOFTWARE DEVELOPMENTS IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401 Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmail.com
- 2. EXISTING SYSTEM: Previous work on string transformation can be categorized into two groups. Some work mainly considered efficient generation of strings. Other work tried to learn the model with different approaches. However, efficiency is not an important factor taken into consideration in these methods.The existing work is not focus on enhancement of both accuracy and efficiency of string transformation. PROPOSED SYSTEM: String transformation has many applications in data mining, natural language processing, information retrieval, and bioinformatics. String transformation has been studied in different specific tasks such as database record matching, spell ing error correction, query reformulation and synonym mining. The major difference between our work and the existing work is that we focus on enhancement of both accuracy and efficiency of string transformation. Modules : 1. Registration 2. Login 3. Spelling Error Correction 4. String Transformation 5. String mining
- 3. Modules Description Registration: In this module an Author(Owner) or User have to register first,then only he/she has to access the data base. Login: In this module,any of the above mentioned person have to login,they should login by giving their emailid and password . Spelling Error Correction: In this module if an user wants to check the spelling, He/She can check it and correct it automatically. String Transformation: Here we are techniques for searching the String 1)String Generation,2)String Transformation. String Generation: It means we have generated 50,000 Strings in alphabetical order.From a to z like a,aa,…..z. String Transformation:
- 4. It means we have given the user with the benefit of String Generation as well as String alias .It will be useful for the user for example if the end user have typed “TKDE” its equal to “Transactions on Knowledge and Data Engineering”. String mining: The User has to download the string with its meanings also He/She can download its substrings and its reverse etc.Also check the given string which is present in the bunch of strings,if its present the result will be “String Found” otherwise ”String NotFound”. System Configuration:- H/W System Configuration:- Processor - Pentium –III Speed - 1.1 GHz RAM - 256 MB (min) Hard Disk - 20 GB Floppy Drive - 1.44 MB Key Board - Standard Windows Keyboard Mouse - Two or Three Button Mouse
- 5. Monitor - SVGA S/W System Configuration:- Operating System :Windows95/98/2000/XP Application Server : Tomcat5.0/6.X Front End : HTML, Java, Jsp Scripts : JavaScript. Server side Script : Java Server Pages. Database : My sql Database Connectivity : JDBC. Conclusion: In this paper, we have proposed a new statistical learning Approach to string transformation. Our method is novel and unique in its model, learning algorithm, and string generation algorithm. Two specific applications are addressed with our method, namely spelling error correction of queries and query reformulation in web Search. Experimental results on two large data sets and Microsoft Speller Challenge show that our method improves upon the baselines in terms of accuracy and efficiency. Our method is particularly useful when the-problem occurs on a large scale.