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Natural Language Processing of the Hybrid Context For Tweet Segmentation

Author(s):

Kanchan Varpe , SPCOE , OTUR , PUNE; Kanchan Varpe, SPCOE OTUR PUNE; Sandip Kahate, SPCOE OTUR PUNE

Keywords:

Twitter, Segmentation, Hybrid Seg, NER

Abstract

A time-line based framework for topic summarization is in the Twitter. Summarization on the topics by sub-topics along time line to fully capture rapid topic evolution can be done on Twitter. An HybridSeg can be in corporate to local context knowledge with global knowledge bases for better tweet segmentation on the social network communication. HybridSeg can having of two phases: first step, the existing NER algorithms are applied to on the batches of tweets. The NERs are then employed to guide the tweet segmentation process. Second step, Hybrid-Seg can be manage the tweet segmentation results iteratively by exploiting all kind of segments in the batch of tweets. Experiments on two tweet datasets show that HybridSeg significantly improves tweet segmentation quality compared with the state of the art algorithm.

Other Details

Paper ID: IJSRDV4I41083
Published in: Volume : 4, Issue : 4
Publication Date: 01/07/2016
Page(s): 1256-1259

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