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EXISTING SYSTEM

PROPOSED SYSTEM

   EXISTING CONCEPT:-

In the existing system existing approaches mostly focus only on text-based summary, microblog summarization with multiple media types (Ex: Text, Image, and Video) is scarcely explored

Most of the previous MDS techniques are designed for well-organized texts, such as news articles

PROPOSED CONCEPT:-

In the proposed system we propose a multimedia social event summarization framework to automatically generate visualized summaries from the microblog stream of multiple media types.

We conduct extensive experiments on two real-world microblog datasets to demonstrate the superiority of the proposed framework as compared to the state-of-the-art approaches.

   EXISTING TECHNIQUE:-

MDS techniques.

PROPOSED TECHNIQUE:-

latent semantic analysis (LSA) technique

    TECHNIQUE DEFNITION:-

Previous MDS techniques are designed for well-organized texts, such as news articles. However, two challenges make it greatly difficult to directly apply the traditionalMDS techniques to summarize microblogs

TECHNIQUE DEFNITION:-

Latent semantic analysis (LSA) technique to select highly ranked sentences; and a hierarchical LDA-style model is utilized in to represent content specificity as a hierarchy of topic vocabulary distributions and then sentences are selected according to these distributions.

    DRAWBACKS:-

Eliminating the potentially noisy images from rawmicroblog image collection.

 Server cluster can handle only one type  request at a time so that load balancing problem occurs

ADVANTAGES:-

With the development of microblogging, many works have shifted their focus to process microblog data.

Cross-media framework for automatically detecting social events and retrieving related candidate microblogs.