An Intelligent Information Retrieval System for Finding Contextual Information on Twitter

被引：0

作者：

Gupta, Rahul ^{[1
]}

Kumar, Akshi ^{[1
]}

机构：

[1] Delhi Technol Univ, Dept Comp Sci Engn, New Delhi, India

来源：

2017 INTERNATIONAL CONFERENCE ON INNOVATIONS IN CONTROL, COMMUNICATION AND INFORMATION SYSTEMS (ICICCI-2017) | 2017年

关键词：

Summarization; Ranking; Context; Relevant; Twitter;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Today lot of rich & opinionated data is available on social micro blogging websites like Twitter. Though the data plays an integral role of contemplating the behavior of the crowd much of it is scattered. The underlying model is an attempt to retrieve information from this data and consequently discover knowledge in the context of the user based on his/her comments about a trending event or hash-tag. The proposed model uses basic mining approaches like keyword-extraction, ranking of tweets and summarization of data to meet the objective. The work has been empirically tested for seven hash-tags and an average precision of 0.514 was attained.

引用

页码：535 / 539

页数：5

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