There are two main categories of multi-document summarization: term-based and ontology-
based methods. A term-based method cannot deal with the problems of polysemy and …

Sentence-based multi-document summarization is the task of generating a succinct
summary of a document collection, which consists of the most salient document sentences …

Multidocument summarization addresses the selection of a compact subset of highly
informative sentences, ie, the summary, from a collection of textual documents. To perform …

Text summarization and classification are core techniques to analyze a huge amount of text
data in the big data environment. Moreover, as the need to read texts on smart phones …

Domain ontology, as a conceptual model, provides a meaningful framework for semantic
representation of textual information. In this paper, we explore the feasibility of using the …

Hurricane Sandy affected the east coast of US in 2012 and posed immense threats to
businesses, human lives and properties. In order to minimize the consequent loss of a …

The data from pre, post and during disasters play a very important and vital role while
immediate decision making in emergency management. Data availability, analysis, and …

With the exponential growth of the usage of web map services, geo-data analysis has
become more and more popular. This article develops an online spatial data analysis and …

In disaster management, a myriad of news and reports relevant to the disaster may be
recorded in the form of text document. A challenging problem is how to provide concise and …

This paper explores the idea of government emergency response and disaster management
through the lens of popular social media services. One of the traditional challenges to …