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EXISTING SYSTEM

PROPOSED SYSTEM

EXISTING  CONCEPT: -

In existing approach the Multi-Document Summarization problem as if it were to be a possible application of what we call the general data merging problem. The general data merging problem refers to every problem where one tries to merge or fuse data.

The scope of the problem when we try to generate a multi-document summarization, we enable the possibility to use techniques that have already been created to merge data in general.

PROPOSED CONCEPT: -

In proposed implementation specifies with a merge function that tries to optimize the weighted harmonic mean between the correctness and the completeness of the suggested solution with relation to the source, the f_β-optimal merge function.

The f_β-optimal merge function, a function newly introduced here, that uses the weighted harmonic mean to find a balance between precision and recall.

EXISTING TECHNIQUE:-

Point-wise Merge Function

PROPOSED TECHNIQUE:-

f_β-Optimal Merge Function

TECHNIQUE DEFINITION:-

Point-wise merge functions take the union of all sources M as input, thus adding up all multiplicities for each element, without making any distinction between the sources the element came from.

TECHNIQUE DEFINITION:-

f_β-optimal merge function that uses the weighted harmonic mean to find a balance between precision and recall. The global precision and recall measures are defined by means of a triangular norm receiving local precision and recall values as an input, in order to generate a multiset of key concepts that we can use to generate summarizations.

DRAWBACKS:-

MDS has some merging problems.

Performance was very slow due to collapse of data.

ADVANTAGES:-

There is no any merging problem occurred.

Performance was high.