Sampling, information extraction and summarisation of Hidden Web databases

Sampling, information extraction and summarisation of Hidden Web databases

Hidden Web databases maintain a collection of specialised documents, which are dynamically generated in response to users’ queries. The majority of these documents are generated through Web page templates, which contain information that is often irrelevant to queries. In this paper, we present a system designed to detect and extract query-related information from documents sampled from database...

A Novel Technique for Data Extraction from Hidden Web Databases

Summarisation of Spoken Audio through Information Extraction

Automatic summarisation of spoken audio is a fairly new research pursuit, in large part due to the relative novelty of technology for accurately decoding audio into text. Techniques that account for the peculiarities and potential ambiguities of decoded audio (high error rates, lack of syntactic boundaries) appear promising for culling summary information from audio for content-based browsing a...

Information Discovery, Extraction and Integration for the Hidden Web

In this paper, we report our initial investigations on the problems of automatically extracting data objects from a given hidden-web source (i.e., the web site with an HTML search form) and automatically assigning semantics to the extracted data. We also propose some future work to address the problem of information discovery and integration for hidden-web sources.

Searching for Hidden-Web Databases

Recently, there has been increased interest in the retrieval and integration of hidden Web data with a view to leverage high-quality information available in online databases. Although previous works have addressed many aspects of the actual integration, including matching form schemata and automatically filling out forms, the problem of locating relevant data sources has been largely overlooke...