Images are important information carriers which are often used in email messages and web pages to attach textual information. In Born digital compound image (BDCI) text and graphics/pictures come together on digital devices having certain distinct characteristics like low resolution (easy for online transmission and to display on screen) and text is created digitally on image. Text from BDCI ca...

Internet content today is about 80% text-based. No matter static or dynamic, the information is encoded and presented as multilingual, unstructured natural language text pages. As the Semantic Web aims at turning Internet into a machine-understandable resource, it becomes important to consider the natural language content and to assess the feasibility and the innovation of the semantic-based ap...

We consider the problem of modeling the content structure of texts within a specific domain, in terms of the topics the texts address and the order in which these topics appear. We first present an effective knowledge-lean method for learning content models from unannotated documents, utilizing a novel adaptation of algorithms for Hidden Markov Models. We then apply our method to two complement...

In this demo proposal, we describe our prototype application, SIERRA, which combines text-based and content-based image retrieval and allows users to link together image content of varying document granularity with related data like annotations. To achieve this, we use the concept of superimposed information (SI), which enables users to (a) deal with information of varying granularity (sub-docu...

one of the oldest medical schools in the world is ayūrvedic school or indian traditional medicine whose history goes back to five thousand years ago. this school, which was formed and came to maturity in india, has affected on other medical schools in the world and iranian medical school has been affected by it. in remnant texts of one of the eastern middle iranian languages, khotanese, in east...

We perform a quantitative analysis of data in a corpus that specialises on summarisation for Evidence Based Medicine (EBM). The intent of the analysis is to discover possible directions for performing automatic evidence-based summarisation. Our analysis attempts to ascertain the extent to which good, evidence-based, multidocument summaries can be obtained from individual single-document summari...

A frequent challenge for many Text Understanding Systems is to tackle the variety of text characteristics in born-digital and natural scene images to which current OCRs are not well adapted. For example, texts in perspective are frequently present in real-word images, but despite the ability of some detectors to accurately localize such text objects, the recognition stage fails most of the time...