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Annotating streams of heterogeneous data for topic generation

by Postdoctoral Researcher on Feb 06, 2013

  • 966 views

Talk given at the VU University Amsterdam, NL - February 6, 2013 ...

Talk given at the VU University Amsterdam, NL - February 6, 2013

Abstract: Since the advent of Linked Data, we have observed a dramatic increase of structured data sources published on the Web. They provide mainly entity to entity interconnections, resulting in a Web of Linked Entities, disambiguated through URIs, spanning structured and unstructured data. Several efforts have been made to exploit such a mine of information for enhancing text understanding, by connecting pieces of text to real world objects, i.e. entities, that are easily discoverable by intelligent agents, resulting in a proliferation of different systems for text annotation through "Web" entities.

In this perspective, we have developed a framework for harmonizing the access to such systems and their output results. The NERD ontology [1] aligns the difference in the annotations and provide a definition for a set of axioms taken from the long tail distribution of common classes among the used extractors. Powered on top of the NERD ontology, we have developed NERD [2] which implements a combined logic that looks for minimizing the error of annotation taking the best, when possible, from these extractors. We have observed that the well-known entity classes, such as Person, Location, Organization are well covered from these extractors, while Event is less, mainly due to a lack of definition and knowledge about what are events. As a follow-up of the Eventmedia project [3], we are defining an event spotter which takes advantage from the large event graph knowledge described in the Eventmedia dataset [4].

Sources of structured and unstructured data are also social platforms. They constantly record streams of heterogeneous data about human’s activities, feelings, emotions, conversations opening a window to the world in real-time. Making sense out of these streams is extremely challenging. We are currently investigating the role of named entities as centroids for micropost topic generations, presenting
them through visual galleries.

[1] - http://nerd.eurecom.fr/ontology
[2] - http://nerd.eurecom.fr
[3] - http://eventmedia.eurecom.fr
[4] - http://eventmedia.eurecom.fr/sparql

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Annotating streams of heterogeneous data for topic generation Annotating streams of heterogeneous data for topic generation Presentation Transcript