FoRESEE 2014: Big Data and Semantic Technologies in Backend and Frontend of
Search Engines aims at analysing and integrating vast amounts of data and
semantic technologies in search engines. This workshop will discuss state-
of-the-art approaches and methodologies regarding industrial as well as
research interests.

Focus
1. Big Data and Search (Backend)
Search Engines are prime examples of Big Data technology. In addition to
processing huge amounts of data, its storage, analysis and management are
central issues of Big Data. Various crawling, mining, linking and
integration methods form the basis of every modern search technology.
Nowadays, search engines exceed classic keyword-based document retrieval by
leveraging semantic technologies such as question answering, user context
inception and conversational interaction. Furthermore, semantic datasets
such as the Linked Open Data Cloud are freely available, supporting
knowledge acquisition at scale.
Intelligent linking of knowledge to answer a specific search need by using
geospatial information, multimedia and social data is regarded as key to
the satisfaction of the user information need.

2. Human-Semantic Interaction and Human-Computer Interaction (Frontend)
Visually well represented search results are an important factor for the
success of a search engine. Next to presenting large amount of data to the
user, we focus on the integration of semantic technologies in Web-
Interfaces. Traditional non-semantic search engines demand different
interfaces.
Data from knowledge bases, such as the Google Knowledge Graph, needs
special representation. In particular, the semantic component of the query
needs to be explicitly depicted. Semantic entities have to be conveyed in
an adequate way by a smart interaction design.
Resulting user data generated inside the browser can be intercepted and be
further utilized to optimize the search interaction. Client-side data
comprises mouse cursor movement, page visits and clicks on certain results.
For instance, this data enables improving ranking results iteratively.
Additionally, the increasing vast amount of data requires stream-based
technologies to handle resulting information efficiently.

The aforementioned description can be expanded by the following points:

Big Data and Semantic Search
- Analysis of Linked Data and the Internet of Things
- Management and efficient storage
- Big Data analytics, e.g., Map-Reduce algorithms
- Recommender Systems
- Architectures and frameworks for Semantic Search using Big Data
- Non-relational storage solutions (NoSQL)
- Data cleansing, integration and Best Practices
- Combining Web technologies with Big Data and Semantic Web
- Social, semantic, explorative and multimedia search
- Query processing and result ranking
- (Industrial) use cases

Human-Semantic Interaction and Human-Computer Interaction
- Visual representation of Linked and Big Data
- Interfaces for representing natural language queries
- Mobility and Semantic Search
- Cutting-Edge and rising technologies for HCI
- Best Practices for representing semantic data
- Integration of implicit and explicit user feedback
- (Industrial) use cases

This listing raises no claim of completeness. Contributions handling topics
other than the mentioned ones will be considered as well as if they fit the
context of the workshop.

The paper submission deadline is the 06. May 2014.
More information can be found on our website http://foresee.unister.de/