ESAIR'13: Sixth International Workshop on Exploiting Semantic Annotations in Information Retrieval

Call for Papers

Please submit your Research/Position Paper (2+1 pages) to be presented as boaster and poster at the workshop!

Exploiting Semantic Annotations

There is an increasing amount of structure on the Web as a result of modern Web languages, micro-formats and linked data, user tagging and annotation, and emerging robust NLP tools. These meaningful, semantic, annotations hold the promise to significantly enhance information access, by increasing the depth of analysis of today's systems. Currently, we have only started exploring the possibilities and only begin to understand how these valuable semantic cues can be put to fruitful use. To complicate matters, standard text search excels at shallow information needs expressed by short keyword queries, and here semantic annotation contributes very little, if anything.

The main questions for the workshop are: How to make use of the currently emerging knowledge resources (such as DBpedia, Freebase) as underlying semantic model giving access to an unprecedented scope and detail of factual information? How to include annotations beyond the topical dimension (think of reading level, prerequisite level, content credibility, transaction trustworthiness, freshness, genre, sentiment, etc) that contain vital cues for matching the specific needs and profile of the searcher at hand?

Many Open Questions

The Workshop will bring together researchers working with semantic annotations, its use cases, its sources (authoring to NLP tools), its users, and its use in DB, IR, KM, or Web research, and work together on a range of open questions:

• Application/Use Case: What are use cases that make obvious the need for semantic annotation of information? What tasks cannot be solved by document retrieval using the traditional bag-of-words? What is keeping searchers from exploring these powerful search request? What impact has the web of data with more and more information in preprocessed form?
• Annotations: What types of annotation are available? Are there crucial differences between author-, software-, user-, and machine-generated annotations? Do we annotate types/classes/categories ("person") or instances ("Albert Einstein")? How similar or different are linked data and annotated text? What are the limitations of the current annotations schemes, and how to overcome them?
• Rich Context: Do we annotate text? Or also search requests and interactions, and their broader context? Besides personalization and geo-positional information, mobiles have a wide and growing range of locational, mechanical and even biometrical sensor data available to them. Can kick-start the query by inferring task and situational context in the mobile use case?
• (Un)certainty: How should we interpret the annotations? Can we reliably link textual annotations to known entity catalogs? Can expect a messy world to be captured in a clean set of meaningful categories? Or is all information fundamentally uncertain and only partly known? How can we fruitfully combine information retrieval and semantic web approaches?

These and other related questions will be discussed at this open format workshop -- the aim is to provide paths for further research to change the way we understand information access today!

We Need Your Help!

Help us shape the future of information access by increasing the depth of analysis of today's systems:

• Submit a short 2+1 page research or position paper explaining your key wishes or key points,
• and take actively part in the discussion at the Workshop.

What's a 2+1 page paper?

We like short and focused contributions highlighting your main point, claim, observation, finding, experiment, project, etc, (roughly 2 pages of mainly text) but we also like clear tables, graphs, and full citations (that's the "+1" page). So your submission can up three pages, as long as max. 2 of them are narrative text.

SCHEDULE

CREDITS

This workshop will be held as part of the 22nd ACM International Conference on Information and Knowledge Management, San Francisco, 2013. Information on San Francisco can be found in the Wikipedia.