Sixth workshop on exploiting semantic annotations in information retrieval (ESAIR'13)

There is an increasing amount of structure on the web as a result of modern web languages, user tagging and annotation, emerging robust NLP tools, and an ever growing volume of linked data. These meaningful, semantic, annotations hold the promise to significantly enhance information access, by enhancing 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. ESAIR'13 focuses on two of the most challenging aspects to address in the coming years. First, there is a need to include the currently emerging knowledge resources (such as DBpedia, Freebase) as underlying semantic model giving access to an unprecedented scope and detail of factual information. Second, there is a need to include annotations beyond the topical dimension (think of sentiment, reading level, prerequisite level, etc) that contain vital cues for matching the specific needs and profile of the searcher at hand.

[1]  Omar Alonso,et al.  Exploiting entities in social media , 2013, ESAIR '13.

[2]  Dan Yang,et al.  Using semantics to process legal document updates , 2013, ESAIR '13.

[3]  Salvatore Orlando,et al.  Dexter: an open source framework for entity linking , 2013, ESAIR '13.

[4]  Se-Jong Kim,et al.  Hierarchical subtopic mining for topic annotation , 2013, ESAIR '13.

[5]  Karin Friberg Search using semantic framenet frames as variables , 2013, ESAIR.

[6]  Davide Buscaldi,et al.  YaSemIR: yet another semantic information retrieval system , 2013, ESAIR '13.

[7]  Egon L. van den Broek,et al.  Recall oriented search on the web using semantic annotations , 2013, ESAIR '13.

[8]  Hengbin Yan Annotation of clausal functional information for semantic retrieval , 2013, ESAIR '13.

[9]  Neel Guha Course specific search engines: a study in incorporating context into search , 2013, ESAIR '13.

[10]  Viktors Garkavijs Learning user's intent using user tags: intelligent interactive image search system , 2013, ESAIR '13.

[11]  Maurice van Keulen,et al.  Named entity extraction and disambiguation: the missing link , 2013, ESAIR '13.

[12]  Jean-Pierre Chevallet,et al.  Wikipedia-based semantic query enrichment , 2013, ESAIR '13.

[13]  Krzysztof Janowicz,et al.  Thoughts on the complex relation between linked data, semantic annotations, and ontologies , 2013, ESAIR '13.

[14]  AlonsoOmar,et al.  Exploiting semantic annotations in information retrieval , 2008 .

[15]  Gilles Falquet,et al.  A user-centric model to semantically annotate and retrieve scientific documents , 2013, ESAIR '13.