Kavita Ganesan

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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(More)
The deployment of Web 2.0 technologies has led to rapid growth of various opinions and reviews on the web, such as reviews on products and opinions about people. Such content can be very useful to help people find interesting entities like products, businesses and people based on their individual preferences or tradeoffs. Most existing work on leveraging(More)
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 modified(More)
Segmentation of clinical texts is critical for all sorts of tasks such as medical coding for billing, auto drafting of discharge summaries, patient problem list generation and many such applications. While there have been previous studies on using supervised approaches to segmentation of clinical texts, these existing approaches were trained and tested on a(More)
Our goal in participating in the TREC 2009 Entity Track was to study whether relation extraction techniques can help in improving accuracy of the entity finding task. Finding related entities is informational in nature and we wanted to explore if inducing structure on the queries helps satisfy this information need. The research outlook we took was to study(More)
The current approaches for linking information across sources, often called record linkage, require finding common attributes between the sources and comparing the records using those attributes. This often leads to unsatisfactory results because the sources are often missing information or contain incorrect or outdated information. We are addressing this(More)
Opinions on the web present a wealth of information that can be leveraged in our day to day decision making tasks ranging from which product to purchase to which doctor to consult for a particular ailment. Due to the large volume of opinions available from different sources across web, digesting all the available opinions is a time consuming process which(More)