opinion summarization

Opinosis Text Summarization Web API

The Opinosis REST API is available to all academic researchers. You can use a command line tool like cURL to access the API or you can also easily access the API from any programming language using HTTP request and response libraries.

Opinion Driven Decision Support System (ODSS)

Opinion Driven Decision Support System (ODSS), Ganesan, Kavita A. , PhD Thesis, University of Illinois at Urbana-Champaign, 07/2013, (2013)

Opinion Driven Decision Support is a term that I coined as part of my Ph.D. thesis refering to the use of large amounts of online opinions to facilitate business and consumer decision making. The idea in my thesis is to combine the strengths of search technologies with opinion mining and analysis tools to provide a powerful decision making platform.

Micropinion Generation: An Unsupervised Approach to Generating Ultra-Concise Summaries of Opinions

Micropinion Generation: An Unsupervised Approach to Generating Ultra-Concise Summaries of Opinions, Ganesan, Kavita A., Zhai ChengXiang, and Viegas Evelyne , Proceedings of the 21st International Conference on World Wide Web 2012 (WWW '12), (2012)

Abstract

This paper presents a new unsupervised approach to generating ultra-concise summaries of opinions. We formulate the problem of generating such a micropinion summary as an optimization problem, where we seek a set of concise and non-redundant phrases that are readable and represent key opinions in text. We measure representativeness based on a modifi ed mutual information function and model readability with an n-gram language model. We propose some heuristic algorithms to efficiently solve this optimization problem.

Opinosis Textual Opinion Summarization Library (Command Line Jar)

The Opinosis Summarizer Software is a demo version of a summarizer that generates concise abstractive summaries of highly redundant text. It  was primarily used to summarize opinions, and thus it can  be regarded as a opinion summarization software.

Opinosis: A Graph Based Approach to Abstractive Summarization of Highly Redundant Opinions

Opinosis: A Graph Based Approach to Abstractive Summarization of Highly Redundant Opinions, Ganesan, Kavita A., Zhai ChengXiang, and Han Jiawei , Proceedings of the 23rd International Conference on Computational Linguistics (COLING '10), (2010)

Abstract

We present a novel graph-based summarization framework (Opinosis) that generates concise abstractive summaries of highly redundant opinions. Evaluation results on summarizing user reviews show that Opinosis summaries have better agreement with human summaries compared to the baseline extractive method. The summaries are readable, reasonably well-formed and are informative enough to convey the major opinions.

Mining tag clouds and emoticons behind community feedback

Mining tag clouds and emoticons behind community feedback, Ganesan, Kavita A., Sundaresan Neelakantan, and Deo Harshal , WWW '08: Proceeding of the 17th international conference on World Wide Web, Beijing, China, p.1181–1182, (2008)

Download Paper

http://dl.acm.org/authorize?943606

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