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EXISTING SYSTEM

PROPOSED SYSTEM

EXISTING CONCEPT:-

All these data mining and text mining techniques hold the assumption that the user’s interest is only related to a single topic. However, in reality this is not necessarily the case.

The number of returned patterns is huge because if a pattern is frequent, then each of its sub patterns is frequent too. Thus, selecting reliable patterns is always very crucial

PROPOSED CONCEPT:-

User information needs are generated in terms of multiple topics each topic is represented by patterns

Patterns are generated from topic models and are organized in terms of their statistical and taxonomic features;

The most discriminative and representative patterns, called Maximum Matched Patterns, are proposed to estimate the document relevance to the user’s information needs in order to filter out irrelevant documents

EXISTING TECHNIQUE:-

Latent Dirichlet Allocation.

PROPOSED TECHNIQUE:-

Novel Information Filtering Model.

TECHNIQUE DEFINITION:-

LDA is a typical statistical topic modeling technique and the most common topic modeling tool currently in use. It can discover the hidden topics in collections of documents using the words that appear in the documents.

TECHNIQUE DEFINITION:-

An Information filtering system is a system that removes redundant or unwanted information from the documents.

DRAWBACKS:-

Stores important parts of data.

It is highly efficient and scalable.

ADVANTAGES:-

Excellent in document modeling.

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