Mashup 2014 - AI Mashup Challenge 2014

AI Mashup Challenge 2014 - CFP
Topics Of Interest
The AI mashup challenge accepts and awards mashups that use AI technology, including but not restricted to machine learning and data mining, machine vision, natural language processing, reasoning, ontologies in the context of the semantic web. Such services may run on any medium, including web browsers, handheld devices, mobile phones (IOS, Android), etc. Imagine for example:
Information extraction or automatic text summarization to create a task-oriented overview mashup for mobile devices
Semantic Web technology and data sources adapting to user and task-specific configurations
Semantic background knowledge (such as ontologies, WordNet, Freebase or Cyc) to improve search and content combination
Machine translation for mashups that cross-language borders
Machine vision technology for novel ways of aggregating images, for instance mixing real and virtual environments
Intelligent agents taking over simple household planning tasks
Text-to-speech technology creating speech mashups with intelligent and emotional intonation
Speech-to-text technology for interactive speech mashups and multimodal services
The display of Pub Med articles on a map based on geographic entity detection referring to diseases or health centers
The integration of enterprise data - see Open Mashup Alliance.
The emphasis is not on providing and consuming semantic markup, but rather on using intelligence to mashup these resources in a more powerful way. For more ideas have a look at last year's AI Mashup 2013 Challenge.
Mashups
A mashup is a lightweight (web) application that offers new functionality by combining, aggregating and transforming resources and services available on the web. Combination alone is not enough to call it a mashup. Consider, for example, visiting a site that is written in a foreign language. Simultaneously using a dictionary in order to translate certain words is not a mashup. A possible mashup would be a new service allowing to click on a foreign word and simultaneously get it translated.
For example MICI is a mashup which demonstrates how situational awareness in emergency management can be raised by pointing to critical infrastructure near emergencies. MICI uses live fire call data from data.seattle.gov and enhances it with information about nearby objects from Linked Geo Data.
A mashup overview as well as a long list of mashable items can be found at programmableweb. For those of you that prefer to read a book, you can take a glance at Ogrinz's Mashup patterns, Hanson's Mashup strategies or Shanahan's Amazon.com Mashups. There are also mashup guides for specific services like Flickr or Yahoo!.
Participants of the 2011 and 2012 challenges contributed to an (e)book “Semantic Mashups - Intelligent Reuse of Web Resources”. It was published by Springer.