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. clubcf - A clustering based collaborative filtering approach for big data application

ABSTRACT

This short paper reports review on collaborative filtering which uses clustering algorithms. Nowadays Service relevant data become too big to be effectively processed by traditional approaches, so one solution to this challenge is Clustering Based Collaborative Filtering. This approach recruits similar services in the same cluster to recommend services collaboratively. Keywords: Big data, Clustering, Collaborative Filtering, Portioning, Recommender systems

EXISTING SYSTEM:

Collaborative Filtering In this module rating similarity between two services is computed by using Pearson correlation coefficient (PCC).Then neighboring services are selected by using Constraint Formula. In last step all recommended services are ranked in nonascending order according to their predicted ratings.

PROPOSED SYSTEM:

Clustering based collaborative filtering approach contains tow modules. First Clustering, in this services are clustered depend on similarity in Description, Functionality & Characteristics respectively. Second Collaborative Filtering, in this, first rating similarity is computed & then predicted rating is given to the clustered services.Clustering In step clustering first stem words are recognized by using Porter Stemmer Algorithm. Then similarity in services based on Description & Functionality is Computed By using Jaccard similarity coefficient (JSC). Characteristic similarity between two services is computed by using weighted sum of Description Similarity and Functionality Similarity. At last services are clustered using Agglomerative Hierarchical Clustering Algorithm.

Modules desciptionMODULES DESCRIPTIONUSER MODULE: In this module, user should register their details and get the secret key for login and user can download the clients uploaded files the users are able to access the content stored in the cloud, depending on their access rights which are authorizations granted by the client, like the rights re-store the modified data in the cloud. CLIENT MODULEIn this module, a client makes use of providers resources to store, retrieve and share data with multiple users. A client can be either an individual or an enterprise. Client can check the uploaded file he can neglate or upload the file Client can view the deduplicate file based on this client can delete the unwanted datas.

CSP MODULE:In this module csp can view all the user details, client uploads details, clients details And clients activities regarding the A Secure Client Side Deduplication Scheme in Cloud Storage EnvironmentsDEDUPLICATION MODULE:In this module, the clients uploaded files can be stored in cloud database.it can be very secure clients can view the file from the database based on the deduplicate factor it can be very secure.SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:System : Pentium IV 2.4 GHz.Hard Disk : 40 GB.Floppy Drive: 1.44 Mb.Monitor: 15 VGA Colour.Mouse: Logitech.Ram : 512 Mb.

SOFTWARE REQUIREMENTS:

Operating system : Windows XP/7.Coding Language: C#IDE:.netDatabase:SQL