A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf
.
Tweet Segmentation and Named Entity Recognition
2016
unpublished
Twitter has involved lots of users to share and distribute most recent information, resulting in a large sizes of data produced every day. However, a variety of application in Natural Language Processing and Information Retrieval (IR) suffer harshly from the noisy and short character of tweets. Here, we suggest a framework for tweet segmentation in a batch mode, called HybridSeg. By dividing tweets into meaningful segments, the semantic or background information is well preserved and without
fatcat:icbombuwfbapno3njhdxr24qsu