Mashup Pubs publication categorizer

The deep web contains an order of magnitude more information than the surface web, but that information is hidden
behind the web forms of a large number of web sites. Meta-search engines can help users explore this information by
aggregating results from multiple resources, but previously these could only be created and maintained by programmers.
In this paper, we explore the automatic creation of meta-search mash-ups by mining the web interactions of multiple
web users to find relations between query forms on different web sites. We also present an implemented system called

Enterprise mashup scenarios often involve feeds derived from
data created primarily for eye consumption, such as email, news,
calendars, blogs, and web feeds. These data sources can test the
capabilities of current data mashup products, as the attributes
needed to perform join, aggregation, and other operations are
often buried within unstructured feed text. Information extraction
technology is a key enabler in such scenarios, using annotators to
convert unstructured text into structured information that can
facilitate mashup operations.

Increasingly large numbers of situational applications are being created by enterprise business users as a by-product of solving day-to-day problems. In efforts to address the demand for such applications, corporate IT is moving toward Web 2.0 architectures. In particular, the corporate intranet is evolving into a platform of readily accessible data and services where communities of business users can assemble and deploy situational applications.

Distributed programming has shifted from private networks to the Internet using heterogeneous Web APIs.

Damia is a lightweight enterprise data integration service where line of business users can create and catalog high value data feeds for consumption by situational applications. Damia is inspired by the Web 2.0 mashup phenomenon. It consists of (1) a browserbased user-interface that allows for the specification of data mashups as data flow graphs using a set of operators, (2) a server with an execution engine, as well as (3) APIs for searching, debugging, executing and managing mashups.